WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

The Opportunity

At Zeta Global, identity is at the core of our marketing cloud. The Identity team builds and operates backend services that power the Zeta Identity Graph - collecting, resolving, and maintaining billions of behavioral, demographic, and transactional signals. These services enable people-based marketing at scale, ensure trust and transparency in how identity data is managed, and provide critical APIs and event streams consumed across Zeta’s platform. Our systems support more than 235 million consumer profiles and process billions of events monthly, requiring services that are highly available, low-latency, and built to scale

We are looking for a Lead Software Engineer who brings strength in both backend distributed systems and data engineering. In this role, you’ll design APIs and event-driven services, scale our systems to handle rapidly growing data volumes, and modernize our platform for resilience, transparency, and performance.

You Will:

• Design and build backend services and APIs for identity resolution, graph transparency, and integrations.
• Develop and optimize event-driven pipelines and workflows processing billions of signals.
• Deploy and operate cloud-native services on EKS/Kubernetes, leveraging Helm for repeatable deployments.
• Ensure reliability, observability, and scalability across services and data pipelines.
• Collaborate across engineering, product, and data teams to deliver end-to-end identity solutions.
• Mentor engineers and influence architecture and roadmap

You Have:

• 5+ years of experience in backend and/or data engineering at scale.
• Strong skills in Python, Java, or Scala, with expertise in APIs, distributed systems, and event-driven design.
• Hands-on experience with Kafka (or similar), Spark/Hive/Flink, and workflow schedulers (Airflow/Luigi).
• Proficiency with Kubernetes (EKS preferred) and deployment practices (Helm, service meshes).
• Solid knowledge of SQL, data modelling, and cloud platforms (AWS).
• Familiarity with columnar / NoSQL databases (Aerospike, Snowflake, HBase, Scylla, Couchbase).
• Strong communication skills and a track record of driving technical direction and mentoring teams.

Bonus Skills:

• Experience with large-scale or multi-tenant distributed systems.
• Exposure to real-time streaming frameworks (Flink, Storm).
• Knowledge of open table formats (Iceberg, Hudi, Delta Lake).
• Background in security, compliance, or privacy related to identity systems.

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $150,000 - $200,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-DD1

ABOUT THE TEAM

We build robots that find other robots and knock them out of the sky. At a time when air superiority can no longer be taken for granted, the Air Defense (AD) Team provides mission critical capabilities to warfighters. From detection to tracking, identification, deterrence, and defeat, our family of networked sensors and effectors enables our customers to rapidly close the kill chain against a broad range of Unmanned Aerial System (UAS) threats. Working across product, engineering, sales, logistics, operations, and mission success, the Air Defense team develops, tests, deploys, and sustains the Anduril Air Defense Family of Systems (FoS) in challenging operational environments worldwide.

ABOUT THE JOB

We are seeking a Senior Mission Data Platform Engineer to design, build, and operate the foundational data infrastructure that empowers our analytics and engineering teams. In this role, you will be the architect of a scalable, reliable, and easy-to-use platform that enables analytics engineers, data scientists, and software engineers to build high-impact analyses and data-driven applications.

You will combine deep expertise in cloud infrastructure, DevOps, and modern data systems to create a cohesive ecosystem. Applying Site Reliability Engineering (SRE) principles will be key to ensuring the performance and availability of these critical systems, which operate in both commercial cloud and classified environments. You will collaborate closely with platform users to understand their needs and remove friction, ensuring our data capabilities are a force multiplier for the entire organization. Your ability to deploy and maintain these mission-critical solutions will be essential, with occasional travel required for real-world implementation and support.

Key Responsibilities:

• Lead the design, development, and maintenance of a scalable, self-service data platform that serves as the foundation for analytics and data applications across the organization.
• Architect and manage the underlying cloud infrastructure using Infrastructure-as-Code (Terraform), containerization (Docker, Kubernetes), and CI/CD best practices to support the data platform.
• Partner with and empower platform users—including analytics engineers, data scientists, and software engineers—by providing robust tooling, clear documentation, and a seamless developer experience.
• Implement SRE principles to ensure the data platform is highly available, performant, and observable, establishing SLOs, automating operational tasks, and leading incident response for the platform.
• Evolve the platform's architecture by evaluating and integrating new technologies from the modern data stack to meet the ever-changing needs of the business.

REQUIRED QUALIFICATIONS

• 6+ years of experience in a combination of data platform engineering, cloud infrastructure, DevOps, or SRE roles.
• Active U.S. Department of Defense (DOD) Secret Clearance or higher and experience operating in air-gapped, classified, and/or other highly constrained network environments.
• Hands-on experience building and maintaining platforms with key components of the modern data stack, such as data lakehouse technologies (e.g., Apache Iceberg), query engines (e.g., Trino/Presto, AWS Athena), transformation tools (e.g., dbt), and real-time stream & batch processing platforms (e.g., Apache Kafka, Apache Spark).
• Extensive experience with Infrastructure-as-Code (IaC), particularly Terraform, for managing complex cloud environments (e.g., AWS, Azure, GCP).
• Strong proficiency in DevOps and software deployment practices, including containerization and orchestration (e.g., Docker, Kubernetes, Helm), GitOps & CI/CD tooling (e.g., ArgoCD, CircleCI), and observability/monitoring/APM platforms (e.g., Datadog, Grafana).
• Exceptional problem-solving and critical-thinking skills, with the ability to architect robust technical solutions for ambiguous and dynamic platform requirements.
• Excellent written and verbal communication skills, especially when communicating with a technical audience; an affection for documentation and a user-centric mindset.
• Procedural fluency in writing, debugging, profiling, testing, and maintaining performant Python and SQL code.
• Experience with data pipeline orchestration tooling (e.g., Flyte, Airflow, Dagster).
• Experience writing code in another language (e.g., Go, Java, Scala, JavaScript/TypeScript).

PREFERRED QUALIFICATIONS

• Ability to comprehend and appropriately modify software written in a systems or lower-level language such as C/C++, Rust, Zig, etc.
• Experience with setting up and managing infrastructure to support analytical workloads on-premises or in resource-constrained environments.
• Experience working with specialized data formats (e.g., MCAP, HDF5) common in domains like robotics.
• Experience with the Nix (dependency management & system configuration) ecosystem.
• Strong Linux fundamentals and troubleshooting skills.
• Prior defense, aerospace, or intelligence domain experience.
• Deep intellectual interest in the intersection of infrastructure, analytics, and the physical hardware world, motivated by our mission.
• Exposure to the technical, programmatic, and operational challenges of developing and deploying advanced systems across various command echelons.

ABOUT THE TEAM

The People Analytics team is at the forefront of transforming how we understand and optimize our workforce. We are a dynamic group of analytical thinkers and storytellers who leverage advanced analytics and robust methodologies to create strategic insights from complex HR data. Collaborating closely with HR Business Partners, Program Management Teams, Business Operations, Talent Acquisition and various cross functional stakeholders we provide actionable insights that drive informed decisions across the entire employee lifecycle; from optimizing talent acquisition and development to enhancing engagement and retention. Our work directly shapes a thriving employee experience, fuels organizational growth, and ensures our people strategy is truly data-driven.

ABOUT THE JOB

This role is central to our People Data & Analytics team, where you will be instrumental in building and maintaining the robust data infrastructure that powers our strategic insights. You'll own the full data lifecycle, from ensuring accurate ingestion and integration of diverse HR data sources, to designing, developing, and optimizing data models and pipelines. Your primary objective will be to transform raw, disparate information into clean, reliable, and analytics-ready datasets, empowering our People Analysts and business stakeholders to unlock deeper understanding of our workforce, enhance employee experience, and drive data-driven decision-making. Success in this role requires a strong technical foundation, meticulous attention to data quality, and a passion for crafting efficient data solutions.

WHAT YOU'LL DO

• Design, build, and optimize robust ETL/ELT pipelines to reliably ingest, integrate, and transform diverse people data from various HR systems (HRIS, ATS, LMS, etc.) into our data platform.
• Develop, maintain, and govern scalable and secure data models, schemas, and ontologies specifically for people analytics, ensuring data quality, consistency, and accessibility for downstream consumption.
• Contribute to the strategic design, development, and evolution of our people data platform and tooling, advocating for engineering best practices, automation, and a scalable analytics ecosystem (e.g., leveraging SQLMesh, Iceberg, Flyte).
• Partner closely with People Analysts, HR Business Partners, and other stakeholders to understand their analytical needs and translate them into robust data solutions, providing well-structured, documented, and reliable datasets.
• Implement and monitor data quality checks, identify discrepancies, troubleshoot data issues, and ensure the reliability and integrity of people data across all systems.
• Continuously monitor the performance of data pipelines and models, identifying bottlenecks and implementing solutions to ensure the efficiency and scalability of our people data infrastructure.
• Create and maintain comprehensive documentation for data pipelines, models, and processes, and champion data engineering best practices (e.g., version control, testing, CI/CD) within the team.
• Implement and enforce strict data security measures and ensure all data handling practices comply with internal policies and external regulations (e.g., GDPR, CCPA) related to employee data privacy.
• Collaborate with broader enterprise analytics and data engineering teams to align on data architecture standards, integrate people data with other business domains, and contribute to the overall evolution of the company's data platform.

REQUIRED QUALIFICATIONS

• 5-7 years of progressive experience in Data Engineering, Analytics Engineering, or a similar role focused on building and optimizing data pipelines and data infrastructure.
• Expert-level proficiency in SQL for complex data manipulation and querying, and advanced Python for scripting, data processing, and automation.
• Extensive experience with cloud-based data warehousing solutions (e.g., Snowflake, Google BigQuery, AWS Redshift, Databricks/Delta Lake) and data lake technologies (e.g., AWS S3, Azure Data Lake Storage).
• Deep understanding and proven experience in designing, implementing, and maintaining robust data models (e.g., dimensional modeling, Kimball methodology) for analytical purposes.
• Hands-on experience building and optimizing complex ETL/ELT processes and data pipelines using modern tools such as dbt, Apache Airflow, Flyte, Dagster, or similar orchestration platforms.
• Excellent communication skills, both written and verbal, with the ability to translate technical concepts for non-technical stakeholders and collaborate effectively across diverse teams.
• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
• Strong technical foundation in data engineering, with expertise in SQL, Python, and experience working with cloud-based data platforms (e.g., AWS, GCP, Azure).

Preferred Qualifications:

• Experience with big data processing frameworks (e.g., Apache Spark, Flink) and advanced data warehousing features like schema evolution or time travel (e.g., Apache Iceberg, Delta Lake).
• Direct hands-on experience with tools mentioned in our stack like Palantir Foundry, SQLMesh, Flyte, or similar cutting-edge data orchestration and transformation platforms.
• Relevant professional certifications from major cloud providers (e.g., AWS Certified Data Analytics - Specialty, Google Cloud Professional Data Engineer).
• Experience with tools like Terraform, CloudFormation, Docker, or Kubernetes for managing data infrastructure and deploying applications.
• Familiarity with integrating data pipelines with leading BI tools (e.g., Tableau, Power BI, Looker) to optimize dashboard performance and data accessibility for end-users.
• Deep expertise working with data from specific enterprise HRIS systems like Rippling, Workday, and Oracle HCM Cloud including their data models and APIs.
• Solid understanding of HR data concepts, metrics, and common HR systems (HRIS, ATS, LMS), with a strong interest in People Analytics.

As a Data Engineer on our BI team, you’ll be a key player in Motive’s growth, delivering the data infrastructure for the AI era. You’ll act as the essential link between complex data and key business domains, delivering the high-quality datasets and semantic models that drive global strategy. This is an exciting opportunity to implement cutting-edge tooling, leverage AI to enhance your workflow, and master a modern data stack in a fast-evolving environment.

This is the perfect role for a "jack of all trades" data practitioner. You’ll design data models, build robust pipelines, manage DevOps and automated systems, and implement AI-driven data tooling. You’ll even get your hands dirty building dashboards and performing deep-dive analysis. If you love working full-stack and owning the entire data lifecycle, you’ll love this role.

What You'll Do:

• Collaborate & Strategize: Partner closely with business stakeholders to understand their challenges and design end-to-end architecture that solves complex business problems.
• Build & Maintain Data Models: Design, develop, and own robust, efficient, and scalable data models in Snowflake and Iceberg using dbt and advanced SQL.
• Orchestrate & Automate: Build and manage reliable data pipelines and CI/CD workflows using tools like Airflow, Python, and Terraform to ensure data is fresh, trustworthy, and infrastructure is version-controlled.
• Champion Data Quality: Implement rigorous testing, documentation, and data governance practices to maintain a single source of truth.
• Enable Analytics & Workflows: Act as the Product Owner and Tech Lead for your data domains, taking responsibility for the end-to-end data product delivery– from raw ingestion to data models enabling analytics and data apps in tools like Tableau and Retool.
• Innovate with AI: Help us build our next-generation data infrastructure by integrating AI capabilities (like Snowflake Cortex AI) to democratize analytics and empower the business.
• Architect Observability: Implement monitoring and alerting frameworks (e.g., dbt packages or  Monte Carlo monitors) to proactively catch "silent" data failures before stakeholders do.

What We're Looking For:

• 6+ years of experience in Analytics Engineering, Data Engineering, or a similar role.
• Deep expertise in SQL and developing complex data models for analytical purposes (e.g., dimensional modeling).
• Hands-on experience with:
  • Data Warehousing: High proficiency in Snowflake (preferred) and experience with Open Table Formats like Iceberg.
  • Data Transformation: dbt
  • Orchestration & ETL: Airflow, Fivetran, Airbyte
  • Cloud Platform: AWS
  • Programming/Ingestion: Python
  • Infrastructure as Code: Terraform
  • AI-Augmented Development: Proficiency using AI coding assistants (Cursor, Copilot, or Claude) to accelerate development and automate routine tasks.
• A strong analytical mindset with a proven ability to solve ambiguous business problems with data.
• Excellent communication skills and experience working cross-functionally.
• Self-starter with the ability to self-project manage work
• A user focus with the ability to understand how a data consumer will use the data products you build

Bonus Points (Nice-to-Haves)

• Experience building semantic models for natural language querying
• Direct experience with advanced Snowflake features (e.g., Snowpark, Cortex AI).
• Experience building visualizations and dashboards in tools like Tableau,  Retool, or Thoughtspot.

Role Overview

We are seeking a Sr. Technical Product Manager to lead the strategy and execution of data product, AI/ML system, AI-powered tooling, and automation initiatives across Patient Experience and Commercial Operations functions. This role is focused on improving how patients navigate testing and billing while enabling operational teams to efficiently progress cases from order to completion. You will play a crucial part in supporting initiatives to reduce friction, improve patient trust, and increase operational efficiency, ultimately driving better conversion, collections, and experience.

This role focuses on building, scaling, and leveraging platforms and products that power decision intelligence and activity orchestration across these domains. You will work in close collaboration with domain leaders while building through centralized Data & AI organization platforms, standards, and governance. You will own the full product lifecycle from discovery through production, ensuring solutions are adopted, trusted, and deliver measurable business impact. In doing so, you will work hands-on as an empowered builder of AI and software solutions to improve workflow efficiency, productivity, and quality for the teams you support.

This is a technical product role requiring fluency in data systems, modern data platforms, ML, and AI implementation patterns (and the ability and drive to build with them directly), combined with strong experience and stakeholder intuition across the associated functions. The role has direct ownership of high-impact initiatives that deeply influence organizational success.

What You’ll Do

Strategy & Roadmap

• Define and own the Data & AI product strategy and roadmap for the Patient Experience + Commercial Operations pod by deeply partnering with business leaders to proactively identify high-impact opportunities, shape problem definitions, and drive aligned priorities
• Translate ambiguous business problems (e.g., stuck cases, fragmented patient communication, support inefficiencies, billing friction) into clear product direction and measurable outcomes
• Own the line between 'what the business needs' and 'what gets built' end-to-end

Discovery, Experimentation, & Requirements

• Develop deep context on the domain so you can proactively propose solutions rather than field requests
• Be hands-on with data: query datasets, review schemas, and validate assumptions through analysis
• Lead end-to-end product discovery with interviews, workflow mapping, data assessments, ROI modeling, etc.
• Define clear product requirements (PRDs, user stories, acceptance criteria) and success metrics
• Design and run experiments to validate product performance and measure causal impact
• Establish leading indicators and KPIs for proactive product and process health assessments

Delivery, Data, & ML Lifecycle

• Partner with data and AI/ML engineering resources to deliver scalable products and capabilities
• Guide development of robust data pipelines and unified data models (360° views across key entities)
• Own the end-to-end ML lifecycle: feature definition, evaluation, deployment, monitoring, drift detection, and retraining
• Ensure training–serving consistency, model versioning, and clear deployment decision gates
• Establish strong observability across data pipelines and models (data quality, latency, reliability, cost)

AI Productization & Hands-On Building

• Define and implement AI product patterns, including agentic workflows and tool/function-calling integrations
• Build process automations and internal tools that improve workflow efficiency, productivity, and output quality for the teams you support
• Establish evaluation frameworks for LLM-powered features (faithfulness, relevance, safety, cost, latency)
• Implement prompt strategies, guardrails, and continuous evaluation pipelines

Governance, Compliance, & Data Quality

• Ensure products meet regulatory and compliance requirements
• Champion data quality, lineage, and reliability through data contracts and observability standards
• Maintain strong documentation practices (e.g., model cards, dataset documentation, audit trails)
• Partner with governance teams (Security, Legal, Compliance, AI Governance) to operationalize AI responsibly

Adoption, Change Management, & Impact

• Launch products with supporting enablement activities to ensure solutions are embedded in workflows with confidence
• Partner with stakeholders to integrate products into proactive, day-to-day decision-making
• Monitor product usage, performance, and business outcomes to iterate based on data and feedback
• Quantify and communicate impact (e.g., revenue lift, cost reduction, cycle time improvements, case completion turnaround)
• Influence Patient Experience and Commercial Operations stakeholders through delivery, not authority

Qualifications

Required

• 7+ years of relevant experience (e.g., product management, applied AI/ML engineering, technical founder, forward-deployed engineering), including 3+ years building data products, AI/ML systems, or related platforms
• Demonstrated domain fluency in Patient Experience and/or Commercial Operations
• Strong understanding of patient journeys, support channels (e.g., chat, voice, call centers), and operational workflows that drive conversion and test completion
• Familiarity with key domain-relevant tooling (e.g., patient portals, support platforms) and associated data
• Strong technical capability (e.g., comfortable scripting, performing EDA, with AI-aided application development)
• Hands-on experience shipping LLM-powered features or automations (e.g., prompting, RAG, tool/function calling, agentic orchestration, evals)
• ML/MLOps literacy (evaluation metrics, experimentation, feature stores, CI/CD, monitoring, drift)
• Familiarity with modern data stacks (e.g., Snowflake, dbt, AWS/SageMaker, Airflow/Dagster)
• Strong stakeholder leadership and communication skills, with the ability to work across technical and business teams
• Experience working in regulated environments (e.g., healthcare, life sciences, fintech)

Preferred

• Experience in healthcare, diagnostics, life sciences, and/or digital health
• Familiarity with healthcare data domains and systems, including patient, provider, payer, claims, billing, and clinical trial data
• Experience with vendor evaluation, platform selection, or external AI tooling ecosystems
• Advanced degree in a technical and/or business discipline

What Success Looks Like

• Production-grade data and AI products are deployed and embedded in day-to-day decision-making workflows
• Process automations and internal tools you build are reducing manual effort and improving output quality across the teams you support
• Measurable improvements seen in key business metrics (e.g., case completion turnaround time, patient satisfaction, cost-to-serve)
• Reliable, high-quality data foundations connect patient, provider, clinical, operational, and billing/financial insights end-to-end
• AI systems are continuously monitored, evaluated, and improved with measurable business impact
• Stakeholders trust and adopt implemented solutions across both corporate and business-unit teams
• Internal teams have transparent access to the function's roadmap, trust in delivery against it, and visibility into the evaluation logic that prioritizes initiatives based on their impact to organizational goals

Role Overview

We are seeking a Sr. Technical Product Manager to lead the strategy and execution of data product, AI/ML system, AI-powered tooling, and automation initiatives across the go-to-market and operational teams embedded within Natera’s core business units (i.e., Oncology, Women’s Health, Organ Health), including Sales, Marketing, and Medical stakeholders. 

This role focuses on building, scaling, and leveraging platforms and products that power decision intelligence and activity orchestration across these domains. You will work in close collaboration with ‘S&M + GM’ leaders while building through centralized Data & AI organization platforms, standards, and governance. You will own the full product lifecycle from discovery through production, ensuring solutions are adopted, trusted, and deliver measurable business impact. In doing so, you will work hands-on as an empowered builder of AI and software solutions to improve workflow efficiency, productivity, and quality for the teams you support.

This is a technical product role requiring fluency in data systems, modern data platforms, ML, and AI implementation patterns (and the ability and drive to build with them directly), combined with strong experience and stakeholder intuition across Sales, Marketing, Medical, and related functions.

This role sits at the intersection of business impact and technical depth, with deep visibility into commercial performance and executive decision-making. You will have direct ownership of high-impact initiatives fueling overall organizational success.

What You’ll Do

Strategy & Roadmap

• Define and own the Data & AI product strategy and roadmap for the S&M + GM pod by deeply partnering with business leaders to proactively identify high-impact opportunities, shape problem definitions, and drive aligned priorities
• Translate ambiguous business problems (e.g., churn risk, campaign performance, clinical profile segmentation, next-best-action orchestration) into clear product direction and measurable outcomes
• Own the line between ‘what the business needs’ and ‘what gets built’ end-to-end

Discovery, Experimentation, & Requirements

• Develop deep context on the domain so you can proactively propose solutions rather than field requests
• Be hands-on with data: query datasets, review schemas, and validate assumptions through analysis
• Lead end-to-end product discovery with interviews, workflow mapping, data assessments, ROI modeling, etc.
• Define clear product requirements (PRDs, user stories, acceptance criteria) and success metrics
• Design and run experiments to validate product performance and measure causal impact
• Establish leading indicators and KPIs for proactive product and process health assessments

Delivery, Data, & ML Lifecycle

• Partner with data and AI/ML engineering resources to deliver scalable products and capabilities
• Guide development of robust data pipelines and unified data models (360° views across key entities)
• Own the end-to-end ML lifecycle: feature definition, evaluation, deployment, monitoring, drift detection, and retraining
• Ensure training–serving consistency, model versioning, and clear deployment decision gates
• Establish strong observability across data pipelines and models (data quality, latency, reliability, cost)

AI Productization & Hands-On Building

• Define and implement AI product patterns, including agentic workflows and tool/function-calling integrations
• Build process automations and internal tools that improve workflow efficiency, productivity, and output quality for the teams you support
• Establish evaluation frameworks for LLM-powered features (faithfulness, relevance, safety, cost, latency)
• Implement prompt strategies, guardrails, and continuous evaluation pipelines

Governance, Compliance, & Data Quality

• Ensure products meet regulatory and compliance requirements
• Champion data quality, lineage, and reliability through data contracts and observability standards
• Maintain strong documentation practices (e.g., model cards, dataset documentation, audit trails)
• Partner with governance teams (Security, Legal, Compliance, AI Governance) to operationalize AI responsibly

Adoption, Change Management, & Impact

• Launch products with supporting enablement activities to ensure solutions are embedded in workflows with confidence
• Partner with stakeholders to integrate products into proactive, day-to-day decision-making
• Monitor product usage, performance, and business outcomes to iterate based on data and feedback
• Quantify and communicate impact (e.g., revenue lift, cost reduction, cycle time improvements, forecasting accuracy)
• Influence across Sales, Marketing, Medical, and GM stakeholders through delivery, not authority

Qualifications

Required

• 7+ years of relevant experience (e.g., product management, applied AI/ML engineering, technical founder, forward-deployed engineering), including 3+ years building data products, AI/ML systems, or related platforms
• Demonstrated domain fluency in Sales, Marketing, Field Medical, and/or related commercial/GTM functions 
• Strong understanding of sales funnel, marketing funnel, medical affairs funnel, and related funnels to relate product ideas to the overall opportunity landscape
• Familiarity with key domain-relevant tooling (e.g., Salesforce) and associated data 
• Strong technical capability (e.g., comfortable scripting, performing EDA, with AI-aided application development)
• Hands-on experience shipping LLM-powered features or automations (e.g., prompting, RAG, tool/function calling, agentic orchestration, evals)
• ML/MLOps literacy (evaluation metrics, experimentation, feature stores, CI/CD, monitoring, drift)
• Familiarity with modern data stacks (e.g., Snowflake, dbt, AWS/SageMaker, Airflow/Dagster)
• Strong stakeholder leadership and communication skills, with the ability to work across technical and business teams
• Experience working in regulated environments (e.g., healthcare, life sciences, fintech)

Preferred

• Experience in healthcare, diagnostics, life sciences, and/or digital health
• Familiarity with healthcare data domains and systems
• Experience with vendor evaluation, platform selection, or external AI tooling ecosystems
• Advanced degree in a technical and/or business discipline

What Success Looks Like

• Production-grade data and AI products are deployed and embedded in day-to-day decision-making workflows
• Process automations and internal tools you build are reducing manual effort and improving output quality across the teams you support
• Measurable improvements seen in key business metrics (e.g., increased sales efficiency, better campaign performance)
• Reliable, high-quality data foundations connect patient, clinical, financial, and commercial insights end-to-end
• AI systems are continuously monitored, evaluated, and improved with measurable business impact
• Stakeholders trust and adopt implemented solutions across both corporate and business-unit teams
• Internal teams have transparent access to the function’s roadmap, trust in delivery against it, and visibility into the evaluation logic that prioritizes initiatives based on their impact to organizational goals
  
  

#LI-DNI

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

The Role 

We’re looking for a Senior Data Engineer to design, build, and operate the data pipelines and aggregates that power Zeta’s AdTech platform. This is a hands-on individual contributor role focused on high-scale batch + streaming data processing, reliable data products, and analytics-ready datasets that enable prediction, agentic workflows, BI reporting, and measurement. You will partner closely with backend, ML, and product teams to deliver trusted, well-modeled data with strong performance, quality, and observability. 

What You’ll Do 

• Build data pipelines: Develop robust batch and streaming pipelines (Kafka/Kinesis) to ingest, transform, and enrich large-scale event data (impressions, clicks, conversions, costs, identity signals). 

• Create data aggregates & marts: Design and maintain curated aggregates and dimensional models for multiple consumers—prediction models, agents, BI dashboards, and measurement workflows. 

• Data modeling & contracts: Define schemas, data contracts, and versioning strategies to keep downstream systems stable as sources evolve. 

• Data quality & reliability: Implement validation, anomaly detection, backfills, and reconciliation to ensure completeness, correctness, and timeliness (SLAs/SLOs). 

• Performance & cost optimization: Optimize compute/storage for scale (partitioning, file sizing, incremental processing, indexing), balancing latency, throughput, and cost. 

• Orchestration & automation: Build repeatable workflows with scheduling/orchestration (e.g., Airflow, Dagster, Step Functions) and CI/CD for data pipelines. 

• Observability for data systems: Instrument pipelines with metrics, logs, lineage, and alerting to accelerate detection and root-cause analysis of data issues.
• Security & governance: Apply least-privilege access, PII-aware handling, and governance controls aligned with enterprise standards.

Qualifications

• 5+ years building production data pipelines and data products (batch and/or streaming) in a high-scale environment.
• Strong experience with SQL and data modeling (dimensional modeling, star/snowflake schemas, event modeling). 

• Hands-on experience with streaming systems (Kafka preferred) and/or AWS Kinesis, including event-driven designs. 

• Proficiency in one or more languages used for data engineering (Python, Java, Scala, or Go). 

• Experience with distributed data processing (Spark, Flink, or equivalent) and performance tuning at scale. 

• Experience with AWS data services and cloud-native patterns (S3, Glue/EMR, Athena, Redshift, etc. as applicable). 

• Familiarity with lakehouse/table formats and large-scale storage patterns (e.g., Parquet; Iceberg/Hudi/Delta are a plus). 

• Experience with orchestration/workflow tooling (Airflow/Dagster/Step Functions) and CI/CD for data workloads. 

• Strong data quality/observability practices (tests, monitoring, lineage; understanding of SLAs/SLOs). 

• Experience with SQL + NoSQL data stores (e.g., Postgres/MySQL; DynamoDB/Cassandra/Redis) and choosing the right store per use case.
• Clear communicator and collaborator; able to work with mixed audiences and translate needs into reliable data interfaces. 

Preferred Experience

• AdTech / programmatic advertising domain knowledge: DSP/SSP/exchange/RTB concepts and data flows. 

• Experience building measurement pipelines (attribution, incrementality, lift, or experimentation analytics).
• Experience supporting ML feature stores, offline/online feature generation, or model training datasets. 

• Experience with real-time analytics stores (Druid/ClickHouse/Pinot) and high-cardinality aggregation strategies. 

• Deep knowledge of data governance/privacy, including PII handling and consent-aware data processing. 

• Open-source contributions, publications, or conference speaking. 

• BS/MS in CS/Engineering or equivalent practical experience. 

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $165,000 - $175,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases

#LI-YW1

About ROLLER

ROLLER is not your average software-as-a-service company. With a global presence in over 30 countries, we're here to bring some excitement to the leisure and attractions industry and make a difference! Our mission is to help businesses operate smoothly and create fun and memorable guest experiences by providing seamless ticketing, point-of-sale, self-serve kiosks, memberships and digital waiver processes.

But here's the best part: our team. We're a group of 300+ highly passionate, enthusiastic, and down-to-earth professionals located all around the world who are all working together to build something truly remarkable. We're aiming high and believe that the possibilities are endless. As we continue to grow globally, we're excited to write our success story and have fun along the way.

We genuinely love what we do, and we're looking for like-minded people to join us on this amazing journey. If you're ready to be part of a dynamic team and make a real impact, come aboard, and let's create some unforgettable experiences together at ROLLER!

About the Role

We are seeking a highly technical, hands-on Senior Data Engineer to architect and scale our data infrastructure from the ground up. As a core member of the data function within our Business Technology team, you will be responsible for building the pipelines and models that power smarter decision-making and operational efficiency across the entire organization.

In this foundational role, you will build & architect the modern data stack, ensuring our infrastructure is robust, automated, and governed. You collaborate as a technical partner with GTM ,Product, Finance, P&C to build high-performance data models and pipelines that transform raw data into actionable cross-functional insights.

Joining ROLLER at this pivotal growth stage, you will have the opportunity to make an outsized impact on our technical landscape, directly influencing how we process data to deliver world-class experiences for our customers globally.

What You'll Do

• Scalable Architecture: Design and implement robust Data Modeling and Architecture strategies that support high-volume data processing and maintain long-term scalability.
• Cloud Ecosystem: Develop and manage end-to-end data pipelines using Google Cloud Platform services, specifically leveraging Cloud Run, Cloud Function for compute, BigQuery for storage, and Cloud Composer (Airflow) for orchestration.
• Transformation Excellence: Build, maintain, and document complex data transformation layers using DBT (Data Build Tool) to ensure high data quality and reliability.
• Infrastructure as Code: Automate the provisioning of cloud resources using Terraform and streamline deployment workflows via GitHub Actions CI/CD pipelines.
• Cloud Data Warehousing: Demonstrate expert-level proficiency in managing and optimizing Cloud Data Warehouses, such as Snowflake & BigQuery.
• Team Collaboration: Partner with cross-functional stakeholders to build and scale high-performing data infrastructure that supports engineering, analytics, and Data Program needs.
• Stack Management: Architect and maintain a modern data stack by implementing best-in-class tools including Snowflake, Bigquery, dbt, Fivetran, Looker, Tableau and Airflow.
• Pipeline Engineering: Develop scalable ETL/ELT workflows and robust data models to deliver real-time analytics and unified business reporting.
• Data Visualization: Create and maintain intuitive, high-performance Looker dashboards will be an added advantage.

About You

You are a technical builder who views data as a competitive advantage. You thrive in fast-paced environments and have a proven track record of engineering scalable data foundations from the ground up. Equal parts architect and analytical problem-solver, you excel at balancing long-term technical vision with the daily hands-on execution of complex pipelines.

You are energized by the full lifecycle of data—moving beyond just writing code to actively leading project discovery and analysis alongside cross-functional partners. You take pride in enabling GTM, Product, Finance & P&C teams through clear insights and high-performance systems. Most importantly, you are excited to act as a founding technical force for a high-growth SaaS company that is transforming the guest experience for attractions businesses globally.

• 5+ years of experience in Data & Analytics or Data Engineering with a focus on Scalable cloud driven data pipeline build

• Proven experience in dimensional modeling (Star/Snowflake schema) and designing architectures that support both historical reporting and real-time needs.
• Expert-level proficiency in Snowflake or BigQuery, including performance tuning, cost optimization, and access control (RBAC).
• Hands-on experience with Google Cloud Platform services, specifically Cloud Function, Cloud Run for containerized workloads and Cloud Composer for orchestration.

• Through hands-on experience of dbt (Data Build Tool) to manage transformations, including writing custom macros, implementing tests, and generating documentation.
• Solid experience using Terraform to provision cloud resources, ensuring that infrastructure is version-controlled and reproducible.
• Proficiency in GitHub Actions to automate testing and deployment pipelines for data models and infrastructure.
• Ability to design high-performance dashboards that prioritize user experience and fast load times.

• Experience collaborating with Finance, GTM, and Product to define key metrics (like CAC, LTV, or Churn) and codifying them into the data layer.
• Familiarity with data ingestion tools like Fivetran , Airbyte, Workato, Mulesoft to sync data from various SaaS platforms into the warehouse.

• Operates as a full-stack Data Engineer with the technical authority to architect and build entire data lifecycles, from raw source ingestion to high-impact data visualization.
• Familiarity with business-critical systems like Salesforce, Chargbee, Gainsight, and product analytics tools.
• Strong communicator with a track record of working across technical and non-technical teams to drive alignment.
• You have a high appetite for Technology and AI and a natural curiosity for how it can transform your work. You’re comfortable using AI tools to automate repetitive 'busy work,' freeing you up to focus on high-impact work.

We believe AI is a career-defining inflection point. ROLLER is a fast adopter of new technology like AI, and every team member is empowered to own their learning and use the latest tools to supercharge their impact. We’re looking for candidates with the proficiency and curiosity to embrace AI and technology — not just as a technical skill, but as a core competency to help us achieve big goals

Preferred Qualifications

• Experience partnering with IT or Business Technology teams to drive cross-functional outcomes.
• Exposure to customer success and revenue workflows, such as onboarding journeys, renewal metrics, or support analytics.
• Familiarity with AI/ML pipelines and experimentation frameworks that support data-driven innovation.

Perks!

• You'll get to work on a category-leading product that customers love in a fun, high-growth industry! Check our Capterra and G2 reviews.
• ROLLER Recharge days to celebrate and recharge once we've hit our goals
• Engage in our 'Vibe Tribe' - led by our team members; you can contribute to company-wide initiatives directly. Regular events and social activities, fundraising & cause-related campaigns...you name it. We're willing to make it happen!
• Team Member Assistance Program to proactively support our team's health and wellbeing - access to coaching, education modules, weekly webinars, and more.
• 16 weeks paid Parental Leave for primary carers and 4 weeks paid Parental Leave for secondary carers.
• Work with a driven, fun, and switched-on team that likes to raise the bar in all we do!
• Individual learning & development budget plus genuine career growth opportunities as we continue to expand!

What You Can Expect

1. Initial call with our Talent Acquisition Manager
   You'll have an initial call with our Talent Acquisition Manager to chat through some of your experience to date, salary expectations and you can check off any initial questions you might have.
2. Interview with the Hiring Manager
   You'll get to meet with the hiring manager to learn more about the role & ROLLER whilst also talking through your experience in more detail.
3. Loop Interviews
   This is where you will get to meet our wider ROLLER team to do a 'vibe check' on us to make sure our culture & vibe meet what you are looking for!
4. Offer
   If all lights are green and the fit feel right, we'll conduct reference checks and you'll receive an offer to join!

Company Overview

ID.me is the next-generation digital identity wallet that simplifies how individuals securely prove their identity online. Consumers can verify their identity with ID.me once and seamlessly log in across websites without needing to create a new login and re-verify. Over 140 million users experience streamlined login and identity verification with ID.me at 20 federal agencies, 44 state government agencies, and 66 healthcare organizations. More than 600 consumer brands use ID.me to verify communities and user segments to honor service and build more authentic relationships. ID.me’s technology meets the federal standards for consumer authentication set by the Commerce Department and is approved as a NIST 800-63-3 IAL2 / AAL2 credential service provider by the Kantara Initiative. ID.me is committed to “No Identity Left Behind” to enable all people to have a secure digital identity. To learn more, visit https://network.id.me.

Role Overview

ID.me is seeking a Staff Data Engineer (SDE-V) to lead the design, build, and operation of the core data infrastructure that underpins our identity platform. This engineer will be responsible for ensuring the reliability, scalability, and performance of the systems that move, process, and store data across the company.

In this role, you’ll own and operate key data infrastructure components — including event streaming platforms, relational databases, and batch processing systems — while driving automation and engineering best practices that improve data platform reliability and developer efficiency. You’ll partner closely with Platform Engineering, Site Reliability Engineering, and Compliance teams to ensure ID.me’s data ecosystem meets demanding operational, security, and regulatory requirements.

This is a hands-on technical leadership role for a data infrastructure engineer who thrives at the intersection of distributed systems, platform engineering, and data operations.

This role is based out of our Mountain View, CA or McLean, VA offices and requires full-time in-office attendance.

Responsibilities

• Own and operate core data infrastructure, including event streaming, relational database, and batch processing platforms.
• Design and implement highly reliable, observable, and scalable data systems that enable real-time and batch data processing.
• Develop automation and guardrails for data governance, retention, and compliance, ensuring auditability and consistency across services.
• Partner with application, platform, and SRE teams to improve data access patterns, reliability SLAs, and recovery processes.
• Establish standards for data infrastructure monitoring, alerting, and capacity planning, ensuring proactive issue detection.
• Drive operational excellence by improving resilience, reducing toil, and implementing self-healing or automated recovery mechanisms.
• Evolve and optimize data pipelines that support downstream analytics, identity verification, and machine learning systems.
• Evaluate, implement, and operate event-driven and batch data platforms such as Kafka, Google Pub/Sub, Dataflow, or Temporal.
• Lead incident response and root cause analysis for production data systems, contributing to postmortems and platform improvements.
• Mentor engineers and advocate for reliability-focused engineering culture across teams.
• Data lake architecture — Design and build the data lake storage and compute topology (object storage, partitioning, lifecycle, tiering) to support batch and streaming workloads.

Minimum Qualifications

• Bachelor’s or Graduate degree in Computer Science, Software Engineering, or a related technical field.
• 8+ years of professional experience in data engineering, software engineering, or distributed systems development.
• 6+ years of programming experience in one or more languages such as Go, Python, or Java, with emphasis on automation and data system integration.

Preferred Qualifications

• Deep expertise in building and operating data systems—including relational databases, streaming, and batch platforms—in production environments.
• Hands-on experience administering and optimizing PostgreSQL or other relational databases in the cloud (AWS RDS, CloudSQL, or AlloyDB).
• Solid understanding of reliability engineering principles, including observability, SLOs, capacity management, and operational readiness.
• Experience managing cloud infrastructure (AWS or GCP) using infrastructure-as-code tools like Terraform, Kubernetes, or Helm.
• Experience operating event streaming platforms such as Kafka or Google Pub/Sub.
• Experience with batch and stream processing systems, including Dataflow, Temporal, or Airflow.
• Strong knowledge of data pipeline orchestration, change data capture, and schema management.
• Background in automation, incident response, and data platform observability.
• Familiarity with data governance and regulatory compliance frameworks (e.g., FedRAMP, GDPR, NIST).
• Contributions to open-source data infrastructure projects or strong community engagement in the data reliability space.
• Passion for performance engineering, system design, and mentoring others to deliver operational excellence at scale.
• AI-assisted development — Demonstrable experience using AI developer tools (e.g., code generation, test generation, query synthesis) to accelerate platform automation while validating outputs through code review and tests.
• Data-aware LLM usage — Ability to safely use large language models for tasks such as SQL generation, data lineage summarization, and runbook drafting while ensuring no sensitive data is exposed to external models and all prompts and outputs are logged for audit.

OVERVIEW

We are seeking a visionary and hands-on Director of Data Engineering to lead our data engineering strategy and execution. This role will be responsible for building and scaling a modern data platform that supports business intelligence, personalization, supply chain optimization, and AI/ML initiatives across the organization.

RESPONSIBILITIES

• Lead and mentor a high-performing team of data engineers and architects.
• Design and implement scalable, secure, and efficient data pipelines and infrastructure.
• Partner with business leaders, product managers, and data scientists to deliver data solutions that drive business impact.
• Oversee the development and maintenance of data lakes, data warehouses, and real-time streaming systems.
• Establish best practices for data governance, quality, and compliance (e.g., GDPR, CCPA).
• Evaluate and implement modern data tools and platforms (e.g., Snowflake, Databricks, Airflow, dbt).
• Drive innovation in data architecture to support personalization, predictive analytics, and AI/ML capabilities.
• Manage vendor relationships and ensure cost-effective use of third-party data services.

QUALIFICATIONS

• 8-10+ years of experience in data engineering or related fields, with at least 5 years in a leadership role.
• Proven experience building and scaling cloud-based data platforms (AWS, GCP, or Azure).
• Expertise in SQL, Python, Spark, and modern data stack tools.
• Strong understanding of data modeling, ETL/ELT processes, and real-time data processing.
• Experience supporting e-commerce, retail, or consumer brands is a plus.
• Excellent communication and stakeholder management skills.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

The base salary range for this position is $250,000-$280,000 per year which represents the current range for the base salary for this exempt position. Please note that actual salaries will vary based on factors including but not limited to location, experience, and performance. As such, on occasion and when applicable, there is the possibility that the final, agreed-upon base salary may be outside of the upper end of the range. Please also note the range listed is just one component of the company’s total rewards package for exempt employees. Other rewards may include performance bonuses, long term incentives, a PTO policy, and many other progressive benefits.

AI Engineer
Location: San Francisco, CA, in-office
Compensation: 150,000 – $210,000
Company: Cargomatic, Inc.

Disruptive, groundbreaking, transformative company is changing an industry

Join a rapidly growing company disrupting the trucking industry! Cargomatic is the #1 technology platform and digital marketplace for powering world-class, local trucking. Take a look around you. Literally everything humans build, grow, or sell has spent time on a truck. Local trucking is the lifeblood of every regional economy, and yet this $82 billion industry still relies heavily on phone calls and fax machines. Cargomatic is transforming the way goods move around every local node in the supply chain by connecting shippers and commercial truck drivers with mobile technology. We are solving complex, real-world problems every day, and giving full transparency to the shipping process. 

AI Engineer- Rapid Prototyping & Automation

Cargomatic is seeking a highly hands-on AI Engineer who thrives in fast-paced environments and is passionate about rapid prototyping and deploying standalone AI-driven applications. This role focuses on building agentic AI systems and automation tools that can operate independently, integrate with our ecosystem, and deliver immediate business value.

You will work at the intersection of AI, product development, and infrastructure- quickly turning ideas into working prototypes and scaling the most promising solutions into production.

Key Responsibilities:

• Rapidly design, prototype, and deploy standalone AI applications that solve real-world logistics and operational challenges
• Build and implement agentic AI systems capable of autonomous decision-making and task execution
• Develop AI-powered automation tools to streamline workflows across operations, customer experience, and internal processes
• Leverage modern LLM ecosystems, including Claude-based and code-first AI frameworks, to build intelligent agents and workflows
• Integrate LLMs, APIs, and data pipelines into production-ready services
• Collaborate with product, engineering, and operations teams to identify high-impact opportunities for AI solutions
• Iterate quickly based on feedback, performance metrics, and evolving business needs
• Ensure scalability, reliability, and security of AI systems in production environments
• Stay current with advancements in AI/ML, especially in agent frameworks, Claude/OpenAI ecosystems, and automation tooling (e.g., n8n)
• Implement guardrails, validation layers, monitoring, and evaluation frameworks to mitigate hallucination, prompt injection, and data security risks.
• Collaborate cross-functionally with Product, Engineering, and Operations to translate business needs into scalable AI-enabled solutions.
• Contribute to architectural standards, technical best practices, and innovation initiatives.

Preferences:

• Strong product builder mindset with an ability to prioritize high-impact solutions
• 3+ years of experience in software engineering, with a focus on AI/ML or automation
• Proven experience building and deploying AI-powered applications or prototypes end-to-end
• Strong understanding of agentic AI concepts, LLMs, and modern AI frameworks
• Hands-on experience with Claude (Anthropic), OpenAI, or similar LLM APIs, including prompt design and orchestration
• Experience with code-based AI frameworks (e.g., Claude tool use / function calling, LangChain, AutoGen, CrewAI, or similar)
• Experience building or orchestrating workflows using n8n (or similar tools like Zapier, Temporal, Airflow)
• Experience with event-driven architectures and real-time systems
• Familiarity with vector databases and retrieval-augmented generation (RAG)
• Proficiency in backend development using Node.js
• Experience with frontend frameworks such as React for building lightweight interfaces
• Hands-on experience with cloud infrastructure, particularly AWS (Lambda, ECS, S3, etc.)
• Familiarity with databases such as MongoDB and RDS (PostgreSQL/MySQL)
• Experience integrating third-party APIs and building microservices
• Ability to move quickly from concept → prototype → production
• Active GitHub contributions or demonstrated passion for emerging technologies in AI and data systems.

Benefits & Perks:

• Competitive compensation
• Medical, dental, and vision benefits
• 401K company match program
• Flexible paid time off (PTO) and paid holiday

ABOUT THE TEAM

As a Senior Data Engineer on the Analytics Team, you will be collaborating with stakeholders across the company to design, build and implement data pipelines and models that enable our next generation of technology to be deployed around the world. You will have a hand in helping shape the data platform vision at Anduril.

ABOUT THE JOB

We’re looking for software and data engineers who are seeking high impact collaborative roles focused on driving operational execution. Ideally you are looking to learn what it takes to build the next generation of defense technology.

WHAT YOU'LL DO

• Lead the design and roadmap for our data platform
• Partner with operations, product, and engineering to advocate best practices and build supporting systems and infrastructure for the various data needs
• Own the ingest and egress frameworks for data pipelines that stitch together various data sources in order to produce valuable data products that drive the business
• Palantir Foundry is our central hub for data driven applications, visualizations and large scale data analysis across the Anduril org. We manage a large user base and provide true data self service at scale.
• We use SQLMesh for data transformations, giving our engineers the ability to work with SQL while enjoying software engineering best practices like version control, testing, and CI/CD for data pipelines.
• For querying data, we utilize Athena, an aws serverless solution that allows our team to run analytics directly on our data lake without managing infrastructure.
• We've implemented Apache Iceberg as our table format, providing advanced data management capabilities like schema evolution and time travel queries.
• We use Flyte for orchestration. It is a highly scalable, kubernetes native modern orchestration platform similar to Airflow or Dagster.

REQUIRED QUALIFICATIONS

• 5+ years of experience in a data engineering role building products, ideally in a fast-paced environment
• You are motivated by our mission. We are working to solve the biggest problems in defense
• Good foundations in Python or another language
• Experience with Spark, PySpark, SQL and dbt
• Experience with Enterprise Data Systems like Palantir Foundry
• Experience with or interest in learning how to develop data services and data products
• Experience with AWS, Azure, or GCP security ecosystem, containerization, and associated tooling
• Knowledge of data & visualization tools, such as Tableau
• Understand the importance of engineering with security’s best practices in mind
• You are empathetic: you are eager to see the world from your users’ perspective
• You’re energized by business impact & a self-starter: you love to drive the direction of ambiguous projects
• Drive to take ownership of and debug complex data transformation pipelines and data models
• Must be a U.S. Person due to required access to U.S. export controlled information or facilities

ABOUT THE TEAM

Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets.

ABOUT THE JOB 

We are seeking a Senior Machine Learning/MLOps Engineer to join the Applied Intelligence team within Maritime Digital Production. You will lead the design, deployment, and sustainment of the AI-enabled backbone that connects data, tools, and people across our digital shipbuilding environment. This role focuses on operationalizing advanced models and architecting the industrial AI stack—selecting, integrating, and standardizing technologies that bring intelligence into production systems only where they deliver real value.

You’ll define and implement core components of the platform, including unified data and feature stores, vector databases, orchestration layers, and model-serving frameworks, while integrating off-the-shelf models for computer vision, OCR/IDP, speech, and retrieval-augmented generation. You’ll work across software, data, manufacturing, and corporate technology teams to translate real factory scenarios—inspection, root-cause analysis, receiving workflows, scheduling—into applied AI capabilities with clear human-in-the-loop controls, auditability, safety gates, and integrations with PLM, MES, CMMS, ERP, and the unified data plane.

This role demands technical range, judgment, and an instinct for when AI is the right tool versus when a simpler logic or workflow solution wins. You’ll collaborate across Anduril in a high-tech, fast-paced culture of innovation focused on delivering systems that work in the real world. If you want to shape how AI becomes a practical, reliable tool for production and logistics at scale, you’ll be helping build the future of digital shipbuilding and the next generation of maritime vehicles.

WHAT YOU’LL DO 

• Architect and own the AI/ML platform stack—from data ingestion, labeling, and feature engineering to model training, deployment, monitoring, and lifecycle management.
• Select, prioritize, and standardize industrial AI components including feature stores, vector databases + RAG, OCR/IDP and CV/STT providers, orchestration layers, and observability systems.
• Build model-serving and inference frameworks optimized for production environments, supporting real-time and batch execution across cloud, edge, and shop-floor systems.
• Translate factory scenarios (receiving, inspection, RCCA, scheduling) into applied AI workflows with defined human-in-the-loop gates, audit trails, and integration contracts with PLM, MES, CMMS, ERP, and the unified data plane.
• Implement event-driven data pipelines and telemetry systems that feed models with contextualized, real-time signals from production and logistics systems.
• Drive make/buy strategy by researching internal and vendor AI capabilities and recommending investments aligned to enterprise roadmaps, Anduril IP principles, and production constraints.
• Define and maintain model governance processes for validation, safety reviews, traceability, and rollback.
• Partner with Maritime platform teams and CorpTech to align architectures with enterprise data standards, ontologies, and compliance policies.
• Lead reliability engineering for deployed models—managing drift detection, retraining triggers, alerting, and operational SLOs.
• Mentor junior engineers and data scientists; establish best practices for MLOps, observability, data management, and secure handling of sensitive production data.

REQUIRED QUALIFICATIONS 

• Strong stakeholder management skills with proven experience aligning engineering, data, and manufacturing teams.
• 8+ years of experience in software or ML engineering with end-to-end delivery of production-grade AI/ML systems.
• Deep experience with MLOps: data acquisition, labeling, curation, pipeline management, model versioning, continuous integration, and model monitoring.
• Strong proficiency in Python and experience with deep learning frameworks (PyTorch, TensorFlow).
• Experience building and deploying containerized ML services using Docker and Kubernetes.
• Proficiency in data engineering, time-series data modeling, and working with semantic/ontology-driven data systems.
• Experience implementing observability for model performance, inference accuracy, and data drift.
• Familiarity with event-driven architectures, IoT/UNS patterns, and real-time systems integration.
• Excellent communication and documentation abilities; able to bridge research, platform, and production domains.
• Eligible to obtain and maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS 

• Experience applying AI/ML within manufacturing, logistics, industrial control, or production environments.
• Background with digital twins, predictive maintenance, OCR/IDP, CV, or STT model integrations.
• Experience with workflow/orchestration tools such as Flyte, Airflow, Kubeflow, or Temporal.
• Familiarity with GPU acceleration (CUDA) and inference optimization (TensorRT, Triton).
• Experience in regulated environments (NNPI/ITAR) and secure model/data governance.
• Demonstrated ability to mentor engineers and set technical direction for AI/ML infrastructure at scale.

ABOUT THE TEAM

The Data & Analytics team builds the core data infrastructure that powers Anduril's operations. We design and implement scalable data architectures that model how Anduril functions across the organization. You will develop high-performance data systems that serve as the digital twin of our operations, creating both the backend services and internal-facing applications that drive mission-critical decision-making. If you are invested in Anduril's mission and interested in building mission-critical data systems, you're in the right place.

ABOUT THE JOB

We're looking for people who excel at building robust data systems. Designing schemas, optimizing performance, and writing the code that powers data-intensive applications. You prioritize engineering excellence and are interested in pushing the boundaries of what data systems can achieve within an organization - never settling for pipelines to dashboards and always pushing the bounds of what is possible . As a Senior Software Engineer, you should be a technical all-star who can take complicated or opaque asks and turn them into business value.

WHAT YOU'LL DO

• Design and implement scalable database schemas and data models that serve Anduril's core operational needs
• Build performant data processing pipelines that transform raw data for dozens of use cases
• Architect end-to-end data solutions - from database design through service layers to integration points to frontend applications
• Collaborate with cross-functional stakeholders to understand complex business requirements and translate them into technical solutions
• Contribute to the technical roadmap for our data systems and help make critical architecture decisions
• Implement and enforce best practices for data integrity, security, and performance optimization
• Build domain expertise in areas such as Finance, Supply Chain, Manufacturing, People, and Sustainment to better design data models
• Be a force multiplier for the Data & Analytics team - embody our principle of Velocity.
• Palantir Foundry is our central hub for data driven applications, visualizations and large scale data analysis across the Anduril org. We manage a large user base and provide true data self service at scale.
• We use SQLMesh for data transformations, giving our engineers the ability to work with SQL while enjoying software engineering best practices like version control, testing, and CI/CD for data pipelines.
• For querying data, we utilize Athena, an aws serverless solution that allows our team to run analytics directly on our data lake without managing infrastructure.
• We've implemented Apache Iceberg as our table format, providing advanced data management capabilities like schema evolution and time travel queries.
• We use Flyte for orchestration. It is a highly scalable, kubernetes native modern orchestration platform similar to Airflow or Dagster.

REQUIRED QUALIFICATIONS

• 5+ years of professional software engineering experience with a focus on data-intensive applications
• Strong experience in database design and optimization
• Proficiency in Python & SQL
• Experience with cloud infrastructure and distributed systems
• Understanding of data modeling concepts and best practices
• Experience implementing security controls for sensitive data
• Ability to drive technical projects from conception to completion in a fast-paced environment
• Excellent communication skills and ability to collaborate with cross-functional teams
• Eligible to obtain and maintain an active U.S. Secret security clearance

ABOUT THE TEAM

The Analytics team is responsible for modeling our internal data into reusable entities that generalize how Anduril operates. From those entities we build workflows, dashboards, and metrics that drive better and faster decision-making. You will work with stakeholders from across the company to understand how Anduril functions and model our data to create the digital twin of our operations. The Analytics space is engrained in our team’s DNA, as we regularly discuss shifts in the industry and keep up with the top relevant blogs. If this culture and Anduril’s mission speaks to you, you’ve found the right place.

ABOUT THE JOB

We’re looking for people who love ontologies - defining domains and writing the code that puts those models into action. Ideally you are passionate about the next generation of defense technology and love building efficient and understandable data models. You prioritize velocity and are interested in pushing the frontiers of what analytics can do within an organization - think data applications rather than just dashboards.

WHAT YOU'LL DO

• Lead the building of Anduril’s ontology for a specific domain such as Finance, Supply Chain, Manufacturing, People, and Sustainment
• Collaborate with stakeholders, collecting requirements, and writing the code that results in Secure, Timely, Accurate, Trusted, and Extensible Data Models
• Seek out problems that can be solved with data and proactively work with the organization to make it a reality
• Become a trusted resource for Anduril leadership in helping them run their organizations more effectively
• Lead the design and roadmap for our data platform
• Partner with operations, product, and engineering to advocate best practices and build supporting systems and infrastructure for the various data needs
• Own the ingest and egress frameworks for data pipelines that stitch together various data sources in order to produce valuable data products that drive the business
• Palantir Foundry is our central hub for data driven applications, visualizations and large scale data analysis across the Anduril org. We manage a large user base and provide true data self service at scale.
• We use SQLMesh for data transformations, giving our engineers the ability to work with SQL while enjoying software engineering best practices like version control, testing, and CI/CD for data pipelines.
• For querying data, we utilize Athena, an aws serverless solution that allows our team to run analytics directly on our data lake without managing infrastructure.
• We've implemented Apache Iceberg as our table format, providing advanced data management capabilities like schema evolution and time travel queries.
• We use Flyte for orchestration. It is a highly scalable, kubernetes native modern orchestration platform similar to Airflow or Dagster.

REQUIRED QUALIFICATIONS

• 5+ years of experience in an analytics focused role - Analytics Engineer, Data Engineer or Analyst / Consultant with a strong engineering background
• Demonstrated experience with autonomy and process ownership
• Experience with data stack tools: dbt, Redshift, Looker/Tableau, Palantir Foundry
• Expert with SQL and experience with Python or other programming languages
• Ability to build world-class data models in a fast, start-up environment
• Demonstrated aptitude for strategic partnerships and communication with non-technical Stakeholders
• Eligible to obtain and maintain an active U.S. Secret security clearance

ABOUT THE TEAM

The Analytics team is responsible for modeling our internal data into reusable entities that generalize how Anduril operates. From those entities we build workflows, dashboards, and metrics that drive better and faster decision-making. You will work with stakeholders from across the company to understand how Anduril functions and model our data to create the digital twin of our operations. The Analytics space is engrained in our team’s DNA, as we regularly discuss shifts in the industry and keep up with the top relevant blogs. If this culture and Anduril’s mission speaks to you, you’ve found the right place.

ABOUT THE JOB

We're looking for people who love delivering value with data - defining ontologies and writing the code that puts them into action. You prioritize velocity and are interested in pushing the frontiers of what analytics can do within an organization - think data applications rather than just dashboards. As a Staff Engineer, you should be a player-coach; your role is to set an example for your team and define what great looks like while also being their advocate & mentor. Your leadership should take a high performing team on towards the next level.

WHAT YOU'LL DO

• There is no such thing as a pure manager at Anduril - you'll demonstrate your ability to be both an IC and a people manager.
• Become the Trusted Partner for end to end date flows - your job doesn't end at the boundary of the data warehouse but instead in the business outcome.
• Become an expert in the domain areas of your direct reports and provide them guidance, mentorship, and support.
• Lead the building of Anduril’s ontology for a specific domain such as Finance, Supply Chain, Manufacturing, People, and Sustainment
• Collaborate with stakeholders, collecting requirements, and writing the code that results in Secure, Timely, Accurate, Trusted, and Extensible Data Models
• Seek out problems that can be solved with data and proactively work with the organization to make it a reality
• Become a trusted resource for Anduril leadership in helping them run their organizations more effectively
• Palantir Foundry is our central hub for data driven applications, visualizations and large scale data analysis across the Anduril org. We manage a large user base and provide true data self service at scale.
• We use SQLMesh for data transformations, giving our engineers the ability to work with SQL while enjoying software engineering best practices like version control, testing, and CI/CD for data pipelines.
• For querying data, we utilize Athena, an aws serverless solution that allows our team to run analytics directly on our data lake without managing infrastructure.
• We've implemented Apache Iceberg as our table format, providing advanced data management capabilities like schema evolution and time travel queries.
• We use Flyte for orchestration. It is a highly scalable, kubernetes native modern orchestration platform similar to Airflow or Dagster.

REQUIRED QUALIFICATIONS

• 6+ years of experience in the analytics ecosystem - Analytics Engineer, Data Engineer or Analyst / Consultant with a strong engineering background
• 2+ years in a Lead role, demonstrating autonomy and process ownership
• Experience managing a team in a dynamic environment with shifting priorities.
• Track record of leading cross-functional technical initiatives with measurable business impact
• Experience working with sensitive data and maintaining security protocols
• Experience with data stack tools: dbt, Redshift, Looker/Tableau, Palantir Foundry
• Ability to build world-class data models in a fast, start-up environment
• Demonstrated aptitude for strategic partnerships and communication with non-technical Stakeholders
• Eligible to obtain and maintain an active U.S. Secret security clearance

ABOUT THE TEAM

As a Staff Data Engineer on the Analytics Team, you will be collaborating with stakeholders across the company to design, build and implement data pipelines and models that enable our next generation of technology to be deployed around the world. You will also shape the current and future vision of the entire data platform. The Analytics space is engrained in our team’s DNA, as we regularly discuss shifts in the industry and keep up with the top relevant blogs. If this culture and Anduril’s mission speaks to you, you’ve found the right place.

ABOUT THE JOB

We’re looking for Software and Data Engineers who are seeking high impact collaborative roles focused on driving operational execution. Ideally you are looking to learn what it takes to build the next generation of defense technology. As a Staff Engineer, you should be a player-coach; your role is to set an example for your team and define what great looks like while also being their advocate & mentor. Your leadership should take a high performing team on towards the next level

WHAT YOU'LL DO

• Lead the design and roadmap for our data platform
• Partner with operations, product, and engineering to advocate best practices and build supporting systems and infrastructure for the various data needs
• Own the ingest and egress frameworks for data pipelines that stitch together various data sources in order to produce valuable data products that drive the business
• Palantir Foundry is our central hub for data driven applications, visualizations and large scale data analysis across the Anduril org. We manage a large user base and provide true data self service at scale.
• We use SQLMesh for data transformations, giving our engineers the ability to work with SQL while enjoying software engineering best practices like version control, testing, and CI/CD for data pipelines.
• For querying data, we utilize Athena, an aws serverless solution that allows our team to run analytics directly on our data lake without managing infrastructure.
• We've implemented Apache Iceberg as our table format, providing advanced data management capabilities like schema evolution and time travel queries.
• We use Flyte for orchestration. It is a highly scalable, kubernetes native modern orchestration platform similar to Airflow or Dagster.
• Operate in a "player-coach" capacity, leading members of the team, while remaining hands on as a contributor

REQUIRED QUALIFICATIONS

• 6+ years of experience in a data engineering role building products, ideally in a fast-paced environment
• 2+ years in a Lead role, demonstrating autonomy and process ownership
• You are motivated by our mission. We are working to solve the biggest problems in defense
• Good foundations in Python or another language
• Experience with Spark, PySpark, SQL and dbt
• Experience with Enterprise Data Systems like Palantir Foundry
• Experience with or interest in learning how to develop data services and data products
• Experience with AWS, Azure, or GCP security ecosystem, containerization, and associated tooling
• Knowledge of data & visualization tools, such as Tableau
• Understand the importance of engineering with security’s best practices in mind
• You are empathetic: you are eager to see the world from your users’ perspective
• You’re energized by business impact & a self-starter: you love to drive the direction of ambiguous projects
• Drive to take ownership of and debug complex data transformation pipelines and data models
• Must be a U.S. Person due to required access to U.S. export controlled information or facilities

ABOUT THE TEAM

As a Senior Data Engineer on the Analytics Team, you will be collaborating with stakeholders across the company to design, build and implement data pipelines and models that enable our next generation of technology to be deployed around the world. You will have a hand in helping shape the data platform vision at Anduril.

ABOUT THE JOB

We’re looking for software and data engineers who are seeking high impact collaborative roles focused on driving operational execution. Ideally you are looking to learn what it takes to build the next generation of defense technology.

WHAT YOU'LL DO

• Lead the design and roadmap for our data platform
• Partner with operations, product, and engineering to advocate best practices and build supporting systems and infrastructure for the various data needs
• Own the ingest and egress frameworks for data pipelines that stitch together various data sources in order to produce valuable data products that drive the business
• Palantir Foundry is our central hub for data driven applications, visualizations and large scale data analysis across the Anduril org. We manage a large user base and provide true data self service at scale.
• We use SQLMesh for data transformations, giving our engineers the ability to work with SQL while enjoying software engineering best practices like version control, testing, and CI/CD for data pipelines.
• For querying data, we utilize Athena, an aws serverless solution that allows our team to run analytics directly on our data lake without managing infrastructure.
• We've implemented Apache Iceberg as our table format, providing advanced data management capabilities like schema evolution and time travel queries.
• We use Flyte for orchestration. It is a highly scalable, kubernetes native modern orchestration platform similar to Airflow or Dagster.

REQUIRED QUALIFICATIONS

• 5+ years of experience in a data engineering role building products, ideally in a fast-paced environment
• You are motivated by our mission. We are working to solve the biggest problems in defense
• Good foundations in Python or another language
• Experience with Spark, PySpark, SQL and dbt
• Experience with Enterprise Data Systems like Palantir Foundry
• Experience with or interest in learning how to develop data services and data products
• Experience with AWS, Azure, or GCP security ecosystem, containerization, and associated tooling
• Knowledge of data & visualization tools, such as Tableau
• Understand the importance of engineering with security’s best practices in mind
• You are empathetic: you are eager to see the world from your users’ perspective
• You’re energized by business impact & a self-starter: you love to drive the direction of ambiguous projects
• Drive to take ownership of and debug complex data transformation pipelines and data models
• Must be a U.S. Person due to required access to U.S. export controlled information or facilities

We are looking for a highly motivated and versatile Senior Platform Engineer to join our platform engineering team. This unique role is central to accelerating our product development lifecycle and operational efficiency. You will be instrumental in bridging the gap between development, infrastructure, and our burgeoning AI/ML initiatives, focusing on automation, self-service infrastructure, and workflow optimization. This position is ideal for an experienced engineer who thrives on creating leverage for others and tackling complex, interdisciplinary challenges.

Key Responsibilities:

CI/CD and Automation

• Design, implement, and maintain scalable and reliable CI/CD pipelines (e.g., using GitLab CI, GitHub Actions, Jenkins, Spinnaker) to ensure rapid and safe deployments across multiple environments.
• Drive the adoption of best practices for build management, testing automation, and deployment strategies (Canary, Blue/Green, etc.).
• Minimize deployment friction and cycle time for all engineering teams.

Self-Service Infrastructure & Provisioning

• Develop and champion self-service tooling and internal platforms (leveraging tools like Terraform, Ansible, Kubernetes, or equivalent cloud provider APIs) that empower development teams to provision and manage their own infrastructure resources securely and efficiently.
• Establish guardrails and policy-as-code to ensure compliance, cost efficiency, and security across all provisioned infrastructure.

AI Infrastructure Enhancement & Support

• Collaborate closely with AI/ML Engineers to improve the underlying platform used for model training, experimentation, and serving.
• Focus on the operationalization of MLOps pipelines, including data lineage tracking, feature store integration, and production model deployment automation.
• Assist in optimizing resource allocation (e.g., GPU usage, specialized hardware) for AI workloads.

Workflow Automation & Internal Tooling

• Architect and build automated workflows and bots, primarily within communication tools like Slack or Zoom, to streamline common engineering tasks (e.g., on-call handoffs, incident response, environment status checks, approval processes).
• Develop internal APIs and services that connect disparate engineering systems to enhance communication and cross-functional transparency.

Required Qualifications

• 5+ years of professional experience in Platform Engineering, DevOps, Site Reliability Engineering (SRE), or a related discipline.
• Deep expertise in cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code tools (Terraform strongly preferred).
• Expertise in containerization and orchestration technologies (Docker and Kubernetes).
• Proficiency in scripting and general-purpose programming languages (e.g., Python, Go, Bash).
• Extensive experience designing and managing CI/CD systems at scale.
• Proven track record of building internal developer platforms or self-service tools.

Preferred Qualifications

• Experience with AI/ML infrastructure, MLOps tooling, or data pipeline technologies (e.g., Airflow, Kubeflow, Vertex AI, SageMaker).
• Prior experience building conversational interfaces, bots, or workflow automation tools for platforms like Slack or Teams.
• Familiarity with distributed tracing, logging, and monitoring systems (e.g., Prometheus, Grafana, ELK stack, Datadog).
• Experience with security best practices in a cloud environment (IAM, network security, secrets management).

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $144,000 - $175,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

The Role

Analytics Engineering at Flex sits at the intersection of Data, Product, Engineering, and business objectives. As Director, Analytics Engineering you will run the team that enables stakeholders at Flex to easily find the data they need to make decisions. You’ll be responsible for developing a world-class analytics platform that powers all data consumption at Flex, as well as managing and developing a team of high-performing Analytics Engineers. You'll also be hands-on, leveraging your technical skills to develop data models and build better data products and solutions. You'll partner with analysts, engineers, PMs and others to define the requirements while being accountable for delivering the end data product.

You Will:

• Develop and lead strategy for data modeling platform and team roadmap
• Manage and mentor a team of Analytics Engineers
• Collaborate with leaders across product & engineering teams to define data requirements and inform architecture/schema design decisions
• Lead the development of data models to consume, transform, and expose data to stakeholders and systems across the company
• Collect business requirements, define successful analytics outcomes, and design data solutions
• Set company-wide standards for data regarding structure, quality, and expectations
• Contribute Flex’s data culture by influencing processes, systems, and tools that enable to make better decisions in a scalable way

You Have:

• 8+ years as an analytics engineer or equivalent, with a track record of shipping high quality products and features at scale
• Expert knowledge of SQL, data warehouses (we use Snowflake), and how to write efficient SQL queries
• Familiarity with common BI tools (preferably Sigma Computing, Tableau, Mode, etc.)
• Expert proficiency with dbt, dbt Cloud, and Airflow
• Strong perspective on analytics engineering development cycle (data modeling, version control, documentation + testing, and best practices for codebase development and CI/CD)
• Proficiency with Python preferred
• Experience within the fintech space preferred

Flex takes a market-based approach to pay, and compensation may vary depending on your primary work location. Work locations are categorized into one of three tiers based on a cost of labor index for that geographic area.  

Tier A (NYC/SF/Seattle): $240,000-290,000
Tier B (Austin, Washington D.C. Philadelphia, Los Angeles, San Diego, Chicago, Miami, Atlanta : $215,000-265,000
Tier C (SLC/All Other States): $200,000-250,000

Offices

Roles posted in New York, San Francisco, or Salt Lake City are hybrid positions with on-site expectations of 2-3 days per week in our local offices. For candidates outside of these areas, you may be eligible for our relocation assistance program.

Who We Are 

Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future.

About the Role

We’re looking for senior engineers to build/scale Nuro's large-scale computing infrastructure in the cloud/data center. This system is the foundation of many critical business applications throughout the company, including but not limited to machine learning data pipelines, data discovery, simulation, and time-series multimedia log processing. In this role, you’ll be working on building a scalable, efficient and reliable system that bridges the gap between fundamental infrastructure and high-level job requests, and make large-scale computations more accessible to autonomy/other infrastructure engineers.

About the Work

• Design and develop scalable, reliable frameworks: BATES to orchestrate and execute large-scale workloads in cloud and on-premise clusters.
• Collaborate with application teams throughout Nuro to provide robust, generic tools and APIs that accelerate their development of business critical applications.
• Optimize workload efficiency and turnaround time by deeply understanding and analyzing application context to identify inefficiencies and bottlenecks, prioritize tasks, and implement innovative solutions

About You

• You have proven experience in building and developing large-scale distributed applications (e.g. Kubernetes).
• You’re self-motivated to identify opportunities for system improvement and drive positive change.
• Ability to turn high-level requirements into a detailed, cohesive system design.
• Willingness to deeply understand application logic across Nuro and a passion for going the extra mile.
• You are highly collaborative and care about creating the best possible user experience.
• You have start-up DNA: You have demonstrated an ability to thrive in the ambiguity of a dynamic, start-up environment or have the DNA to do so
• You possess a bachelor's degree in Computer Science, Electrical Engineering, or a closely related field or equivalent experience

Bonus Points 

• Experience with database technologies (e.g., Redis, SQL, NoSQL) and pub/sub systems.
• Experience with hyperscalers, particularly Google Cloud Platform or other major providers.
• Experience with workflow management tools or map-reduce frameworks such as Apache Airflow, Buildkite, Ray, or Dataflow..
• Experience with Linux system, e.g. CPU scheduler, memory management, file systems
• Experience with data analysis, includes defining metrics, running A/B testing, and building metric dashboards.
• Experience with real-time monitoring framework like Prometheus.
• Experience with continuous integration/delivery (CI/CD)

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $132,300 and $198,450 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. #LI-DNP

Who We Are 

Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future.

About the Role

We’re looking for senior engineers to build/scale Nuro's large-scale computing infrastructure in the cloud/data center. This system is the foundation of many critical business applications throughout the company, including but not limited to machine learning data pipelines, data discovery, simulation, and time-series multimedia log processing. In this role, you’ll be working on building a scalable, efficient and reliable system that bridges the gap between fundamental infrastructure and high-level job requests, and make large-scale computations more accessible to autonomy/other infrastructure engineers.

About the Work

• Design and develop scalable, reliable frameworks: BATES to orchestrate and execute large-scale workloads in cloud and on-premise clusters.
• Collaborate with application teams throughout Nuro to provide robust, generic tools and APIs that accelerate their development of business critical applications.
• Optimize workload efficiency and turnaround time by deeply understanding and analyzing application context to identify inefficiencies and bottlenecks, prioritize tasks, and implement innovative solutions

About You

• You have proven experience in building and developing large-scale distributed applications (e.g. Kubernetes).
• You’re self-motivated to identify opportunities for system improvement and drive positive change.
• Ability to turn high-level requirements into a detailed, cohesive system design.
• Willingness to deeply understand application logic across Nuro and a passion for going the extra mile.
• You are highly collaborative and care about creating the best possible user experience.
• You have start-up DNA: You have demonstrated an ability to thrive in the ambiguity of a dynamic, start-up environment or have the DNA to do so
• You possess a bachelor's degree in Computer Science, Electrical Engineering, or a closely related field or equivalent experience

Bonus Points 

• Experience with database technologies (e.g., Redis, SQL, NoSQL) and pub/sub systems.
• Experience with hyperscalers, particularly Google Cloud Platform or other major providers.
• Experience with workflow management tools or map-reduce frameworks such as Apache Airflow, Buildkite, Ray, or Dataflow..
• Experience with Linux system, e.g. CPU scheduler, memory management, file systems
• Experience with data analysis, includes defining metrics, running A/B testing, and building metric dashboards.
• Experience with real-time monitoring framework like Prometheus.
• Experience with continuous integration/delivery (CI/CD)

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $160,360 and $240,540 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. #LI-DNP

Shopmonkey's vision is to help every shop thrive by equipping them with the tools they need to run and grow their business. Our cloud based all-in-one shop management software takes owners and technicians from quote to cashing out a satisfied customer. Our software has a modern and intuitive UI and our backend is powered by the latest technologies so our clients can focus on the things they do best. As a Senior ML Engineer at Shopmonkey, you will be a part of a globally distributed engineering team working closely with your product and design counterparts. You will have the chance to work on the frontier of ML modeling, data pipelines, MLOps, and agentic AI systems to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver ML powered systems that are not only intelligent but trusted and useful. You’ll move fast to bring ML systems from discovery all the way through production, helping to shape the future of the automotive care experience. For any Bay area based candidates, this would be hybrid with 2-3 days/week office at our Morgan Hill, CA office for collaboration. 

What you will do:

• Design, build, and ship production-ready ML models across a range of problem spaces: regression, classification, clustering, ranking, and recommendation systems.
• Conduct end-to-end development of ML systems: data gathering, experimentation, feature engineering, model training, evaluation, deployment, and monitoring.
• Define and track model performance metrics, run A/B tests, and iterate based on real-world feedback.
• Help design and implement shared feature stores so that reusable features can serve multiple models consistently in both batch and real-time contexts.
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
• Contribute to training infrastructure, model versioning, and CI/CD pipelines for ML workflows.
• Work closely with data scientists and data engineers to develop data driven solutions that are high impact for businesses.
• Translate complex ML workflows into digestible updates for cross-functional stakeholders.
• Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment.
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
• Help build and ship AI agents that help automate key auto-shop business processes.

We are looking for people who have:

• Minimum of 5+ years of industry experience in applied machine learning; advanced degrees (Master’s or PhD) may offset years of experience.
• Proven experience shipping models into production (not just proof-of-concepts or notebooks).
• Proficiency in Python; experience with ML frameworks like PyTorch or Tensorflow.
• Strong foundations in classical ML/DL. Including some of the following: regression, classification, clustering, ranking, feature engineering, model evaluation, and experimentation.
• Bachelor’s degree in a STEM field, or equivalent practical experience.
• Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.

Nice to have:

Candidates should have some experience in one or more of the following areas.

• Understanding of MLOps principles: model versioning, orchestration, evaluation, monitoring, model serving, and CI/CD for ML. 
• Understanding of MLOps, and experience with modern tooling like MLFlow, DVC, Airflow, etc.
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
• Experience with/interest in LLM workflows and agentic workflows
• Cloud infrastructure experience, (e.g. GCP, AWS).
• Familiarity with vector databases (e.g. Pinecone, pgvector) and embedding-based retrieval or similarity search.
• Strong SQL skills for working with large-scale data.
• Experience designing or contributing to feature stores (e.g. Feast, VertexAI Feature Store, Tecton) for shared, reusable feature pipelines.

Bonus Points:

• Prior experience working at a high growth startup.
• Experience building consumer-facing agents in vertical SaaS, in the automotive industry (business or consumers).
• Background in data processing or real-time analytics.
• Experience with Snowflake or other large-scale data warehouse solutions.

In the United States, the range is typically a salary of $165,000 to $200,000 + bonus + equity + benefits. The range provided is Shopmonkey’s reasonable estimate of the base compensation for this role. The actual amount will be based on job-related and non-discriminatory factors such as location, experience, training, skills, and abilities. Consult with your Recruiter during the initial call to determine a more targeted range based on these job-related factors. In addition to this base compensation company stock options and benefits as outlined below are included.

About this opportunity:

At Freenome, we are seeking a Senior Software Engineer II to join our innovative Engineering team. The ideal candidate is an experienced backend engineer with a strong background in developing scalable and reliable software solutions. You will play a crucial role in designing, building, and maintaining backend services that support our mission to detect cancer early. This position requires a collaborative mindset, as you will work closely with an interdisciplinary team of engineers, scientists, and product managers to deliver high-quality software solutions. You are passionate about software development best practices and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to our engineering management team. This role will be a Remote role. 

What you’ll do:

• Design, develop, and deploy reliable, maintainable, scalable, and fault-tolerant backend services that power both our internal and external systems.
• Collaborate with interdisciplinary teams, including scientists, product managers, and other engineers, to solve complex problems and deliver high-quality software solutions.
• Mentor and guide junior engineers, fostering their growth and enhancing the team's technical expertise.
• Lead code and design reviews, champion engineering best practices and promote a culture of quality and collaboration.
• Contribute to the development of data infrastructure for machine learning applications, ensuring efficient data processing and integration.
• Drive the implementation of engineering hygiene practices, ensuring the reliability and maintainability of our systems.
• Advocate for and implement innovative software development methodologies and tools to improve team efficiency and product quality.
  

Must haves:

• Bachelor of Science in Computer Science, Engineering, or related field or equivalent training, fellowship, and/or work experience.
• At least 8 years of experience as part of a software development team successfully shipping software products, including leading projects from end-to-end and mentoring others.
• Proficiency in Python and experience with backend development in a team production environment.
• Strong experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud Platform.
• Proven experience in designing and implementing scalable backend systems, with a focus on reliability and performance.
• Excellent written and verbal communication skills, with a mindful and transparent approach to collaboration.
  

Nice to haves:

• Understanding of statistical and machine learning methods, with practical experience in applying them to real-world problems.
• Expertise in developing ETL or data pipelines that run at scale, utilizing common workflow management systems like Flyte, Airflow, or similar.
• Domain-specific experience in computational biology, genomics, bioinformatics, or a related field.
• Experience working in an FDA regulated environment, with a strong understanding of compliance requirements and best practices.
  

Benefits and additional information:

The US target range of our base salary for new hires is $161,925 - $227,325. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-REMOTE

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Senior Associate, Software Engineer – Data Platform & AI Applications
San Francisco, California 

The Opportunity 

Jordan Park is seeking a Senior Associate to help build and extend our enterprise data platform and AI application ecosystem.

This role combines advanced data engineering, cloud infrastructure, DevOps discipline, and applied AI development. The Senior Associate will operate as a senior individual contributor — owning major platform components while partnering closely with leadership and business teams. This is a hands-on technical role with meaningful scope and influence.

In this role, you will be responsible for enabling trusted analytics across the firm, integrating proprietary data into AI systems, automating operational workflows and creating custom apps and tooling.

Your Role

• Data Platform Engineering
  • Design, build, and maintain production-grade SQL data pipelines (e.g., dbt + Snowflake + Python)
  • Develop and manage orchestration workflows (Airflow or equivalent)
  • Create data ingestion processes and API integrations

• AI Application Development
  • Build and develop the use of AI in the form of: LLM apps, RAG architectures, Custom GPTs & Agent systems
  • Integrate proprietary firm data securely into AI workflows
  • Establish observability standards
  • Translate AI experimentation into production-grade tools

• Cloud Infrastructure (AWS)
  • Support AWS-based infrastructure including VPCs, ECS, EKS, S3, etc.
  • Containerize services using Docker and manage workloads in Kubernetes
  • Establish logging, monitoring standards

• Python Development & Automation
  • Develop Python-based tools for API integrations, data transformations, ad-hoc in-house applications & tooling
  • Build reusable modules and maintain code standards
  • Create automation solutions that reduce manual operational effort

• Projects & Communication
  • Partner cross-functionally with Investment, Client Advisory, Operations, and Finance teams
  • Be self-directed in project management and delivery
  • Translate business requirements into technical architecture
  • Deliver executive-ready summaries of platform and AI initiatives

Qualifications

Required:

• Bachelors degree with 5–8 years of experience in: data engineering, platform engineering, cloud infrastructure
• Requisite experience in AI Application development including LLM APIs and RAG Pipelines
• AWS experience including Docker and Kubernetes
• Advanced Python proficiency
• Advanced SQL and data modeling
• Experience implementing CI/CD and DevOps best practices
• Strong written and executive communication skills
• Experience in wealth management, asset management, or fintech
• A positive, helpful and can-do attitude

Preferred:

• Salesforce data integration experience
• Experience designing secure AI architectures
• Experience mentoring junior engineers

Compensation & Benefits

Compensation at Jordan Park includes a base salary, discretionary year-end bonus, benefits and other perks.  We apply a total reward philosophy when determining compensation terms. The expected base salary for this role in San Francisco, California will range from $125,000 to $160,000 per year commensurate with experience, job-related skills, relevant education, licenses and certifications, and other business and organizational needs. 

Our benefits package includes:  

• Medical, dental & vision insurance – 100% of premium covered for employees
• 401k participation with employer contribution
• Generous paid time off 
• Commuter benefits program (pre-paid tax dollars towards your commute)
• Fitness Reimbursement
• Annual Professional Development Stipend 

Associate, Software Engineer – Data Platform
San Francisco, California

The Opportunity 

Jordan Park is seeking a Technology & Data Engineering Associate to advance our data platform and data quality initiatives. This role operates at the intersection of data engineering, analytics, data quality management, and AI enablement.

The Associate will design, build, and maintain production-grade data systems while partnering directly with executives, investment teams, operations, and client service professionals to drive measurable business outcomes. This is a hands-on technical role with meaningful ownership and visibility.

Your Role

• Data Platform
  • Design, build, and maintain production-grade SQL data pipelines (e.g., dbt + Snowflake + Python)
  • Develop and manage orchestration workflows (Airflow or equivalent)
  • Create data ingestion processes and API integrations
  • Monitor pipeline reliability and performance; proactively resolve issues

• Data Quality & Controls
  • Develop deep expertise in firm data, systems, and processes
  • Design reconciliation frameworks across systems and automate data validation/exception reporting
  • Perform detailed variance analysis and root cause investigations
  • Partner with operations and finance teams to ensure reporting integrity

• Analytics & Business Intelligence
  • Architect and maintain Tableau dashboards used across the firm
  • Train and support internal stakeholders on self-service analytics

• Python Development & Automation
  • Develop Python-based tools for API integrations, data transformations, ad-hoc in-house applications & tooling
  • Build reusable modules and maintain code standards
  • Create automation solutions that reduce manual operational effort

• Projects & Communication
  • Work closely with the Chief Technology Officer (CTO) to deliver clear executive summaries of data findings, operational trends, etc.
  • Document project discovery and project management artifacts
  • Translate technical work into business impact
  • Present findings to senior leadership

Qualifications

Required:

• Bachelors degree with 3–5 years of experience in Data Engineering, Analytics, Business Intelligence or related technical role
• Advanced SQL proficiency (production-level experience)
• Experience with dbt and Snowflake (or similar modern data stack)
• Strong Python skills for data engineering and automation
• Experience with Tableau or similar BI platform
• Strong written and verbal communication skills
• A positive, helpful and can-do attitude

Preferred:

• Experience in wealth management, asset management, fintech, or financial services
• Familiarity with Salesforce reporting and CRM data models
• Experience building AI workflows or internal GPT tools
• Experience with cloud infrastructure (AWS preferred)

Compensation & Benefits

Compensation at Jordan Park includes a base salary, discretionary year-end bonus, benefits and other perks.  We apply a total reward philosophy when determining compensation terms. The expected base salary for this role in San Francisco, California will range from $115,000 to $150,000 per year commensurate with experience, job-related skills, relevant education, licenses and certifications, and other business and organizational needs. 

Our benefits package includes:  

• Medical, dental & vision insurance – 100% of premium covered for employees
• 401k participation with employer contribution
• Generous paid time off 
• Commuter benefits program (pre-paid tax dollars towards your commute)
• Fitness Reimbursement
• Annual Professional Development Stipend 

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond. This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply. If you want to see your work directly change how a company functions — not someday, but now — this is the role.

What you'll do

• Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
• Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
• Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
• Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
• Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
• Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
• Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture

What we're looking for

• 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
• Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
• Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
• Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
• Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
• A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
• Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

While not required, these are a plus:

• Experience with vector databases, embeddings, or semantic search is a plus

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite

OPEN POSITION ANNOUNCEMENT!

Data Engineer

Open until filled.

Posted 4/29/2026 San Diego County – hybrid work schedule set by SDCP

About the role:  The San Diego Community Power (SDCP) is seeking a seasoned Data Engineer to join our growing team of analytics experts who will be responsible for designing, maintaining, expanding, and optimizing our data infrastructure for data collection, management, transformation, and access. A key priority of this role will be to assist in SDCP’s development of centralizing its data eco-system to allow for creation of pipelines that convert raw data into usable formats for data analysts and other data consumers to utilize. The Data Engineer will handle the core data aspects of software engineering and data science and utilize software engineering principles to develop algorithms that automate the data flow process. They will collaborate with data and system analysts to build machine learning and analytics infrastructure from testing to deployment. 

WHO IS SAN DIEGO COMMUNITY POWER?

San Diego Community Power is a community-driven, not-for-profit public agency providing cleaner energy to the San Diego region. Formed in 2019, Community Power is the second largest Community Choice Aggregator (CCA) in California, serving nearly 1 million customer accounts across its member agencies: the Cities of San Diego, Chula Vista, Encinitas, Imperial Beach, La Mesa and National City, as well as the unincorporated areas of San Diego County.  

OUR HISTORY

San Diego Community Power was formed in 2019 as a public, not-for-profit community choice aggregator (CCA) in the San Diego region. We began electric service in 2021 and serve five member agencies: San Diego, Chula Vista, Encinitas, La Mesa and Imperial Beach, County of San Diego, and National City. SDCP was formed to bring local control and customer choice to San Diego while also providing clean and renewable energy at competitive rates. By the end of 2023, SDCP will provide electricity for nearly half the electric load in San Diego Gas and Electric’s service territory and will be the second largest CCA in California. For more information, please visit SDCommunityPower.org.

COMMITMENT TO DIVERSITY

At SDCP, we value diversity and are committed to creating an inclusive environment for all employees. We represent a diverse customer base and hope to hire employees that reflect our communities. We provide equal employment opportunities to all applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. 

ESSENTIAL DUTIES AND PRIMARY RESPONSIBILITES

• Building and maintaining a centralized cloud-based data infrastructure for optimal extraction, transformation, and loading of data from a wide variety of sources. 
• Assemble large, complex data sets that meet functional/non-functional business requirements. 
• Developing data tools and APIs for data analysis. 
• Deploying and monitoring machine learning algorithms and statistical methods in production environments to solve organizational needs. 
• Ensuring data accessibility and security and implementing company data policies regarding data privacy and confidentiality. 
• Improving data systems reliability, speed, and performance. 
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer trends, operational efficiency, and other key business performance metrics. 
• Collaborating with other internal teams, data analysts, and other stakeholders to understand and optimize how data can be leveraged to meet business needs. 
• Assist in drafting data and analytics’ solicitations and in the selection of consultants. 
• Assist with drafting staff reports and presentations for Board and Committee meetings. 
• Performs other related duties and responsibilities as required. 

MINIMUM KNOWLEDGE, SKILLS, AND ABILITES

• Advance working knowledge of SQL, experience working with relational databases, query authoring (SQL) and working familiarity with various databases. 
• Demonstrated experience in developing API and integrations to support analytics in cloud environment. 
• Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. 

• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. 
• Strong analytic skills related to working with unstructured datasets. 
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management. 
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets. 
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores. 
• Good understanding of data architecture, data design, data warehousing and data modeling concepts. 
• Strong project management and organizational skills. 
• Experience supporting and working with cross-functional teams in a dynamic environment. 

PREFERRED KNOWLEDGE, SKILLS, AND ABILITES

• Experience in the energy sector and/or supporting the implementation of programs funded by California state agencies (e.g., California Public Utilities Commission, California Energy Commission, California Air Resources Board).
• Ability to strongly represent the organization in various professional engagement settings from local to national convenings (conferences, workshops, executive meetings, etc.).

PREFERRED QUALIFICATIONS, EDUCATION AND EXPERIENCE

Minimum of two (2) to three (3) years of professional experience in a Data Engineer role, preferably in the energy industry with a graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. The candidate should also have experience using the following software/tools:

• Experience with big data tools: Hadoop, Spark, PowerBI, Kafka, etc.
• Experience with AWS, Azure and Google Cloud services.
• Experience with relational SQL and NoSQL databases.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with open-source technologies: Python, Pytorch, Flask, Tensorflow or Keras
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Java, C++ etc.
• Experience with batch, micro-batching and real-time data ingestion methodologies.
• Experience with GitHub or similar code repositories

WORK ENVIROMENT & CONDITIONS

Prolonged periods sitting at a desk and working on a computer. The position requires occasional carrying, lifting and/or moving objects up to 25 pounds. Occasional local travel required and reliable transportation to be able to attend SDCP events, meetings, and workshops as needed is expected. At SDCP we work in the communities we serve and in the office. SDCP works to ensure a safe and healthy workplace for employees and in our communities. SDCP requires employees to be fully vaccinated for COVID-19. SDCP is an agency required to adopt and promulgate a Conflict-of-Interest Code (“COI”). The COI code requires employees in designated positions, including those identified under the interim disclosure process to file a Statement of Economic Interests (Form 700) on an annual basis. A Successful candidate accepting this position may be required to file Conflict of Interest forms subject to the regulations of the Fair Political Practices Commission.

COMPENSATION: 

Salary Range: The position salary range is: $84,900 - $110,400; with exact compensation to be determined by SDCP, depending upon experience. 

Benefits: Standard benefits package including but not limited to:

Insurance: SDCP offers group health benefits, including medical, vision, and dental insurance, for eligible FT employees. Also provided is a $100,000 Life & AD&D policy, STD and LTD coverage that is 100% paid by SDCP.

Retirement: SDCP offers a 457(b) plan for employee contributions and contributes 10% of eligible compensation to the employee’s Money Purchase Plan.

Paid Time Off: 11 holidays per year + paid winter holiday (between 12/24-12/31), 160 hours of accrued paid time off per year (increases with time in service), and 96 hours per year of accrued paid sick leave.

This job description may not be inclusive of all assigned duties, responsibilities, or aspects of the job described, and may be amended at the discretion of SDCP as needed. 

Strategic Project Lead / Delivery Manager 

Data Annotation & AI Delivery

8+ Years of Experience

Position Overview

We are looking for a seasoned Delivery Manager (8+ years of experience) to lead large-scale data annotation and curation projects in support of cutting-edge LLM and multimodal AI research. You will oversee end-to-end delivery for projects with 100+ team members, ensure world-class data quality, and drive process and tooling innovation in collaboration with AI researchers and cross-functional teams.

This role is ideal for someone who combines deep technical expertise, proven leadership in managing large teams, and a passion for advancing AI/ML innovation. Given that our key customers operate in the data analytics, data engineering, and Business Intelligence (BI) space, the ideal candidate will bring hands-on leadership experience with platforms such as Databricks and Snowflake, enabling them to deeply understand customer domains, speak their language, and deliver annotation outcomes that are contextually relevant and technically sound.

Primary Responsibilities

1. Team Leadership & Development

• Lead, mentor, and grow large-scale teams of annotators and trainers.
• Drive performance management, career development, and targeted training.
• Foster a culture of excellence, ownership, and continuous learning.
• Design and implement motivation strategies (including gamification) to boost engagement and reward top performers.

1. Project Management & Coordination

• Define and manage project scope, objectives, timelines, and quality metrics.
• Align with cross-functional stakeholders on goals and deliverables.
• Proactively identify and resolve delivery risks, blockers, and dependencies.
• Provide clear and consistent reporting on progress, challenges, and solutions.

1. Data Quality & Integrity

• Own quality control and data integrity across the annotation lifecycle.
• Analyze datasets to identify trends, anomalies, and insights for improvement.
• Implement best practices for annotation, evaluation, and data curation.
• Share learnings and continuously improve quality processes.

1. Technical Collaboration & Innovation

• Partner with engineering and research teams to optimize internal tooling.
• Stay ahead of emerging trends in AI, ML, and multimodal processing.
• Champion innovations that reduce task completion times and improve efficiency.
• Maintain clear and scalable documentation for processes and training.

1. Customer & Domain Engagement

• Serve as a domain-knowledgeable point of contact for customers operating in data engineering, analytics, and BI environments.
• Leverage hands-on experience with platforms like Databricks and Snowflake to understand customer data workflows, terminology, and quality expectations.
• Translate customer-specific data engineering and BI contexts into clear, actionable annotation guidelines and quality benchmarks for delivery teams.
• Collaborate with customers to define annotation taxonomies and evaluation criteria that align with their data pipeline and analytics use cases.

Required Skills & Qualifications

• 10+ years of experience in engineering, program management, or delivery of large-scale projects.
• Proven ability to lead and scale large teams (100+ members) with measurable impact.
• Strong technical grounding in AI/ML, data annotation, and multimodal systems.
• Hands-on leadership experience in data analytics, data engineering, or BI domains, with working knowledge of platforms such as Databricks and/or Snowflake (architecture, pipelines, data modeling, and production workflows).
• Familiarity with the modern data stack including ETL/ELT pipelines, data warehouses, data lakes, and BI tools (Power BI, Tableau, Looker, or similar).
• Ability to translate complex data engineering and analytics concepts into annotation frameworks, quality standards, and training materials.
• Proficiency in Python (preferred) or Swift for data analysis and automation.
• Strong mathematical and analytical skills for data-driven problem solving.
• Experience in data curation, annotation pipelines, and quality control.
• Excellent communication and stakeholder management skills.
• Track record of driving high-quality outputs under tight deadlines.

Preferred Skills & Qualifications

• Advanced degree in Computer Science, Data Science, AI, or related fields.
• Experience applying gamification to workforce engagement.
• Familiarity with modern project management tools & methodologies.
• Exposure to state-of-the-art multimodal AI technologies.
• Prior experience managing annotation or data labeling projects for customers in the data engineering, analytics, or BI space.
• Familiarity with SQL at an advanced level and data orchestration tools such as Apache Airflow, dbt, or Prefect.
• Certifications in Databricks (e.g., Data Engineer Associate) or Snowflake (e.g., SnowPro Core) are a plus.

Founded in Silicon Valley in 2009 by Marc Andreessen and Ben Horowitz, Andreessen Horowitz (aka a16z) is a venture capital firm that backs bold entrepreneurs building the future through technology. We are stage agnostic. We invest in seed to venture to growth-stage technology companies, across AI, bio + healthcare, consumer, crypto, enterprise, fintech, games, and companies building toward American dynamism. a16z has $100B+ under management across multiple funds.

We’ve established a team that is defined by respect for the entrepreneur and the company-building process; we know what it’s like to be in the founder’s shoes. We’ve invested in companies like Anduril, Airbnb, Coinbase, Cursor, Databricks, Deel, Figma, GitHub, Roblox, SpaceX, and Stripe. Our team is at the forefront of new technology, helping founders and their companies impact and change the world.

The Role

You will join a team of highly autonomous, senior ICs developing both software capabilities for the firm’s investing and operating functions, and external-facing products for the firm’s partners, portfolio, and investors. This role specifically involves leading the technical strategy, architecture, and implementation of machine learning systems that power the firm’s internal and external-facing applications. You will be responsible for the entire model lifecycle, from feature engineering and training to large-scale, low-latency serving and robust MLOps infrastructure.

The Applied Software Group operates in the mode of an internal startup. We own an exceptionally tight feedback loop and take on requests from all corners of the firm. This is a high-visibility role that requires a clear architectural vision, strong software engineering fundamentals, exacting communication skills, and the ability to engage and educate our firm on the technology we are developing and shipping.

This role requires an in-office presence 2-3 days a week in our San Francisco, CA office.

To join our team, you should be excited to:

• Architect, build, and maintain scalable and reliable ML production pipelines (data, training, and inference)
• Collaborate with the Applied Software Group (ASG) team to integrate ML models into user-facing products serving the investing partnership and our operating teams
• Set and evolve MLOps standards for the team, including producibility, automated testing, CI/CD, observability, and model governance across the firm.
• Research and lead the implementation of model serving strategies (e.g., real-time APIs, batch processing) to meet strict latency and throughput requirements
• Drive the technical roadmap for core ML infrastructure, influencing platform choices and building cloud-native systems primarily on GCP.
• Operate with high autonomy, owning outcomes end-to-end, proactively identifying gaps, and raising the technical bar for the team.
• Set a high standard for code quality and system design, producing clear, principled, and extensible solutions that scale with the firm.
• Bring positive energy in every interaction with the team and foster inclusive collaboration
• Learn the inner workings of VC and work closely with the investing partnership

Minimum Qualifications

• 2+ years of professional experience as a Machine Learning Engineer or similar role.
• Strong mathematical intuition and problem-solving skills
• Expertise in Python and its statistical modeling ecosystem (e.g. NumPy, scikit-learn, etc.)
• Solid experience with major ML frameworks like PyTorch, TensorFlow, or JAX
• Proven experience deploying and managing ML models in a production environment using tools like Kubeflow, MLflow, Airflow, or TFX
• Strong understanding of containerization technologies (e.g., Docker, Kubernetes/GKE) as applied to ML serving
• Familiarity with cloud computing environments (preferably GCP), including data storage and compute services
• Low ego, high empathy, and the capacity to collaborate effectively with diverse teams

The anticipated salary range for this role is between $341,000 - $422,000, actual starting pay may vary based on a range of factors which can include experience, skills, and scope.

This role is eligible to participate in the a16z carry program and various discretionary bonus programs as well as benefit and perquisite plans including health, dental, vision, disability, life insurance, 401K plan, vacation, and sick leave.

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

The Data Scientist I supports statistical analyses of large datasets, the development and deployment of Machine Learning (ML), multimodal Deep Learning (DL), and Artificial Intelligence (AI) solutions that improve the relevance and value of ads across our Ad Exchange, Contextual Platform, and Attention Measurement Platform. This role focuses on applying strong analytical foundations, building and evaluating ML and DL models, leveraging general AI concepts and techniques, while also partnering closely with the Engineering, Product, and Data Science team to improve ad-serving performance, operational decision-making and lead development of new AI products that best serve the business. 

The ideal candidate is curious, data-driven, and eager to develop a strong understanding of the advertising domain and the systems that power large-scale decision-making. You will work with large datasets, contribute to production AI systems, and gain hands-on experience across the ML lifecycle — from exploration to monitoring.

Note: GumGum fosters a flexible work environment, offering GumGummers the ability to work either in-office or remotely/from home. For this position, in-person/office collaboration is required 2 days per week, supporting a balanced approach to flexibility and team engagement.

What You'll Achieve

• Support the translation of business and product requirements into data-driven analyses and ML solutions
• Partner with Engineering team members and senior Data Scientists to develop, test, and deploy ML and DL models
• Conduct exploratory data analysis to inform feature development and modeling approaches
• Build, run, and maintain regular pipelines to analyze production data, generate KPIs, and prepare automatic retraining of existing models
• Query, clean, and structure large datasets using SQL, Spark, and cloud data platforms
• Train, evaluate, and iterate on traditional ML models and multimodal deep learning models under guidance from senior team members
• Design and maintain Looker dashboards and other Business Intelligence (BI) tools to track Key Performance Indicators (KPI) for key stakeholders
• Develop and deploy agentic pipelines and other LLM-powered applications, including prompt engineering, tool use, and evaluation of model outputs
• Contribute to existing Machine Learning Engineering (MLE) workflows for model training, deployment, and monitoring
• Document analyses, models, and broader learning to support knowledge sharing across the team and non-technical audiences
• Continuously expand on statistical and AI foundations while learning new AI/ML techniques, tools, and advertising-domain concepts

Skills You'll Bring

• Bachelor’s degree in a quantitative field (e.g., Statistics, CS, Math, Physics, or Economics).
• 1–2+ years in a data-driven role such as Analytics, Data Science, or ML Engineering.
• Proficiency in Python and experience applying ML/DL methods using libraries like scikit-learn, PyTorch, HuggingFace, or OpenCV.
• Dependable SQL skills and experience designing pipelines or DAGs using tools like Airflow or Astronomer.
• Exposure to cloud environments (AWS/GCP, Databricks, Snowflake) and large-scale query tools like Spark or Snowpark.
• Strong grasp of A/B testing, experimental design, and statistical concepts (regression, classification, optimization).
• Experience with LLM prompting and interest in frameworks like RAG, LangChain, or agentic systems.
• Ability to design dashboards for diverse audiences and collaborate effectively with Product and Engineering teams.

What We Offer

At GumGum, competitive base pay is a part of a total rewards package, which also includes benefits, an emphasis on recognition, development, and wellness. The reasonable estimated base pay range for this role is from $128,000-$130,000 annually. The actual amount may be higher or lower. Individual compensation will vary based on factors including, but not limited to, relevant qualifications, work location, and labor market conditions.

The total rewards package offered also includes an employer-matched 401(k) retirement plan, and, depending on the role, participation in a bonus, commission, or stock incentive program. Your recruiter can share more specifics during the hiring process. Learn more about our U.S. benefits & perks package at gumgum.com/benefits.

We are seeking a highly experienced and passionate Sr Staff Site Reliability Engineer (SRE) to join our growing team. In this critical role, you will be responsible for the reliability, scalability, performance, and security of our core systems and services. You will leverage your extensive expertise in various technologies to design, implement, and maintain robust infrastructure and automation solutions.

Responsibilities

• Implement and maintain the infrastructure and pipeline required for an internal LLM-powered chat service, potentially leveraging platforms like OpenRouter or similar alternatives.
• implement and maintain highly available, scalable, and secure cloud-native infrastructure on Amazon Elastic Kubernetes Service (EKS).
• Develop and implement comprehensive observability strategies, including monitoring, logging, and alerting, to ensure the health and performance of our systems.
• Architect and optimize data pipelines to ensure efficient and reliable data flow across various platforms.
• Drive the continuous improvement of our CI/CD pipelines, promoting best practices for automated testing, deployment, and release management.
• Champion cloud-first strategies, leveraging the full capabilities of cloud platforms for infrastructure, services, and operations.
• Implement and enforce robust security practices across our infrastructure, applications, and data.
• Design and maintain Docker-based containerization solutions for our applications.
• Develop and maintain automation scripts and tools using Python, Bash, and PowerShell.
• Collaborate with development teams to ensure reliability is built into the software development lifecycle from inception.
• Troubleshoot complex production issues across various layers of the stack, identifying root causes and implementing preventative measures.
• Participate in on-call rotations to support production systems.

Qualifications

• 3+ years of experience in Site Reliability Engineering, DevOps, or a similar role with a strong focus on operational excellence.
• Deep expertise in Amazon EKS, including cluster provisioning, management, and troubleshooting.
• Extensive experience with observability tools and practices, including Prometheus, Grafana, ELK stack, or similar.
• Proven track record in designing and implementing robust data pipelines (e.g., Kafka, Airflow, Spark).
• Strong background in CI/CD methodologies and tools (e.g., Jenkins, GitLab CI, ArgoCD).
• Expert-level knowledge of cloud platforms (AWS preferred), including infrastructure-as-code principles.
• Comprehensive understanding of security best practices for cloud environments, applications, and data.
• Proficiency in Docker for containerization and orchestration.
• Advanced scripting and programming skills in Python, Bash, and PowerShell.
• Solid understanding of networking concepts, distributed systems, and operating systems.
• Excellent problem-solving, analytical, and communication skills.
• Ability to work independently and as part of a highly collaborative team.
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Preferred Qualifications

• Experience with other Kubernetes distributions or cloud providers.
• Familiarity with compliance frameworks (e.g., SOC 2, HIPAA, GDPR).
• Certifications in AWS, Kubernetes, or other relevant technologies.

Successful candidates must be able to demonstrate U.S. citizenship, permanent residency, or status as a protected individual to satisfy ITAR, contractual, and/or regulatory requirements.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $133,400 - $200,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

About your role

We are looking for a forward-thinking Data Engineering Intern to join our team for Summer 2026. This isn't just a role about moving data from point A to point B; it’s about rethinking how those pipelines are built. You will sit at the intersection of core infrastructure and AI, building robust ETL processes while leveraging AI technologies to automate the very workflows you create.

Your mission is dual-purpose: you will support our Business Intelligence efforts and directly influence our product roadmap by turning raw data into actionable insights through advanced dashboards and automated workflows.

A Day in the Life

• Build & Orchestrate: Design, develop, and maintain ETL pipelines to ingest data into our Snowflake warehouse using Python, SQL, and Airflow.
• AI-Driven Automation: Implement AI-powered solutions to streamline engineering tasks, including:
• Automating code generation and documentation.
• Building AI-driven data quality checks and anomaly detection.
• Developing "self-healing" pipelines that can identify and alert on ingestion errors.
• Insight Generation: Use Jupyter Notebooks and Streamlit to analyze data and build internal tools that help our product team make data-driven decisions.
• Visualization: Create high-impact dashboards in Tableau that translate complex data into a clear narrative for stakeholders.
• Agile Collaboration: Participate in daily Scrum huddles, manage tasks via Jira, and work closely with product owners and QA to promote code to production.
• Cloud Infrastructure: Interact with cloud services via CLI and manage containerized environments using Docker and Kubernetes.

What you’ll need

• Academic Status: Currently pursuing an undergraduate degree with a targeted graduation date in 2026 or early 2027, or pursuing a degree in Computer Science, Data Science, or a related quantitative field.
• Programming Mastery: Expertise in Python and SQL
• Infrastructure Mindset: A strong understanding of Data Warehousing (Snowflake) and ETL orchestration (Airflow).
• DevOps Curiosity: Familiarity with CLI, Docker, and Kubernetes for managing cloud-based environments.
• Analytical Toolkit: Experience with Jupyter Notebooks, Tableau, or Streamlit.
• Problem Solver: A proactive approach to using AI/LLMs to automate repetitive tasks and improve system reliability.

The Summer "Win"

By the end of your 10-week internship, you will have designed and deployed a functional ETL pipeline that feeds into a custom Insights Dashboard. Your work won't just sit in a folder, it will be used to influence our official product roadmap.

Interview Process

• Recruiter Phone Screen
• Technical Assessment 
• Hiring Manager Interview
• Team Interview

Data at Brex

Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers.

What You’ll Do

As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a wide range of analytic applications. 

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities:

• Design, build, and maintain data models and pipelines that scale with the growing number of services, products, and changes in the company.
• Collaborate closely with Data Scientists, Data Analysts, and Business teams to understand their data needs, translating them into robust, efficient, scalable data solutions that enable ease of predictive analytics, data analysis, and metrics formulation. 
• Maintain data documentation and definitions, building and ensuring that source-of-truth tables remain high quality for data science and reporting applications. 
• Develop and enable integration with various data sources, allowing for more data-driven initiatives across the company.
• Apply best practices in data management to ensure the reliability and robustness of data utilized across various analytics applications.
• Set and proliferate company-wide standards for data relating to structure, quality, and expectations.
• Act as a liaison between the technical and non-technical teams, bridging gaps and ensuring that data solutions align with business objectives.
• Use agentic AI where it speeds up pipeline and quality work, without skipping validation.

Requirements:

• 3+ years of experience in Data Engineering, Data Analytics, or a related field such as Analytics Engineering.
• Advanced knowledge of databases and SQL with the ability to efficiently stage, process, and transform data.
• Experience integrating and orchestrating data workflows with various modern data tools and systems.
• Experience with data modeling, ETL/ELT processes, and data warehousing solutions.
• Experience working with a data warehouse such as Snowflake.
• Experience with a data workflow orchestrator tool such as Airflow.
• Experience with a programming language such as Python. 
• Experience with agentic AI. 
• Exceptional quantitative and analytical skills.
• Strong communication skills and ability to collaborate with various stakeholders, both technical and non-technical.

Nice to have:

• Familiarity with BI tools such as Looker, Tableau, or similar platforms. 
• Solid dbt in production: models, tests, docs, and collaboration in a shared repo. 
• AI-ready data: Metrics and dimensions are clear and reusable so AI-assisted analysis does not fork definitions. 
• Experience with Salesforce data integration. 

Compensation:

The expected salary range for this role is $120,800 - $151,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About This Role

Varda is seeking a Data Engineer to join our team. In this role, you will support the development of data pipelines, storage, security, and quality that power the organization. You will learn and contribute to the current application ecosystem and data architecture. You will collaborate with team members across functions to help identify opportunities for process or application improvements.

You will assist in the implementation of these solutions through the product life cycle from opportunity identification to support and sustainment. You will work cross-functionally with team members across Varda to support initiatives that enhance company processes, execution insight, and infrastructure robustness. Projects will include a wide range of desired outcomes, including cycle time reduction, cost reduction, improved decision making, risk reduction, and any other key operational efficiency. Your contributions will immediately impact functional operations and have an opportunity to contribute to Varda's overall growth and success. This role will report to the Director of Enterprise Applications.

This is a full-time, onsite, exempt position located in our El Segundo headquarters.

Responsibilities

• Assist in building and maintaining ELT pipelines that ingest data from ERP, CRM, PLM, QMS, and other enterprise systems.
• Support enterprise data platform and enterprise application evaluations by researching external solutions and documenting findings.
• Assist with data storage tasks, including table format standards, partitioning strategies, and interoperability across the tool ecosystem.
• Establish data quality frameworks, lineage tracking, and pipeline observability, including SLA monitoring, proactive alerting, and production-grade logging.
• Support AI/ML workflows by designing feature pipelines, clean data products, and a governed knowledge layer that keeps data semantically aligned for reliable model and agent consumption.
• Work with application engineers and functional stakeholders to help translate requirements and business logic into technical specifications and data solutions.
• Operate effectively within regulated environments where your pipelines will be subject to compliance and auditability requirements enforced by FDA GMP, ITAR, and DCAA.
• Implement and enforce modern development practices, including source control, peer review, CI/CD pipelines, and automated build/test/deploy workflows (ex, GitHub Actions).
• Leverage AI-assisted development tooling to accelerate delivery and improve personal productivity.
• Learn and apply layered data architecture patterns to organize data assets for reliability and reuse.

Basic Qualifications

• Bachelor's degree in Computer Science, Information Systems, or related fields. 
• 3+ years of experience in enterprise integration or data engineering roles (advanced degrees count towards years of experience).
• Experience with cloud data warehouse or Lakehouse platforms (ex, Snowflake, Databricks).
• Experience with relational (SQL) and non-relational (NoSQL) databases (ex, PostgreSQL, MySQL, MongoDB, DynamoDB)
• Exposure to data transformation tools (ex, dbt).
• Proficiency in SQL and at least one general-purpose programming language (ex, Python).
• Exposure to Enterprise Systems such as MRP, CRM, ERP, etc.
• Foundational understanding of data modeling concepts (star schema, normalization, dimensional modeling).
• Familiarity with source control (Git) and basic CI/CD concepts.
• Ability to write clean, documented code and a willingness to learn data quality testing practices.
• Understanding of software architecture principles, data warehousing, and ELT workflows.
• Capability to gather business requirements from stakeholders and take a project from initial concept to finished product.
• Ability to work with end users to rapidly iterate on prototype applications by solving end-user issues.
• Ability to translate technical concepts to non-technical audiences for stakeholders, internal and external to the organization.

Preferred Skills and Qualifications

• Experience with database administration, including schema design, performance tuning, and query optimization.
• Experience interfacing with engineering and manufacturing groups to understand system designs and translations to data needs.
• Experience supporting AI/ML pipelines, including feature stores, training data pipelines, or model monitoring infrastructure.
• Experience in a start-up or similar high-growth environment.
• Familiarity with workflow orchestration tools (ex, Airflow).
• Exposure to aerospace, defense, or pharmaceutical data environments.
• Experience working with ERP systems deployed in a design development environment.
• Exposure to Infrastructure as Code for cloud resource provisioning (e.g., Terraform).
• Relevant platform or tooling certifications (ex, dbt Certified Developer, cloud data platform certifications).

Compensation

• Data Engineer: $130,000 - $160,000
• Leveling and base salary are determined by job-related skills, education level, experience level, and job
• performance
• You will be eligible for long-term incentives in the form of stock options and/or long-term cash awards
• Offer compensation also includes the ability to purchase company stock through the Employee Stock Purchase Plan

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a Data Analyst II (DA), you will play a central role in enhancing the operational tracking and reporting capabilities of different business teams across Brex. You will work closely with Data Scientists, Data Engineers, and partner teams to drive meaningful insights for the business through visualizations, self-service tools, and ad-hoc analyses. This is a high-impact role in a fast-paced fintech environment where your work will directly influence strategic decisions.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Apply data visualization and storytelling skills in creating business intelligence solutions (such as Looker and/or Hex dashboards) that enable actionable insights.
• Perform ad-hoc analyses and deep dives to investigate business questions, surface trends, and provide data-driven recommendations.
• Develop self-service data tools and processes that empower business stakeholders to independently monitor the performance and health of their respective areas.
• Collaborate closely with Data Scientists and Data Engineers to identify data sources, enable data pipelines, and support the development of analytical data models that operationalize reports and dashboards.
• Implement and maintain rigorous data quality checks to ensure the integrity and robustness of datasets used across dashboards, reports, and analyses.
• Partner with various departments—including Sales, Operations, Product, and Finance—to understand their data needs and deliver tailored analyses and reporting that support strategic planning.
• Contribute to the automation of recurring analyses and reporting workflows using Python.

Requirements

• 3+ years of experience in data analytics or a related role in a professional setting.
• 2+ years of experience working directly with Sales, Operations, Product, or equivalent business teams.
• Fluency in SQL to manipulate data and perform complex analyses (CTEs, window functions, joins across large datasets).
• Experience with Python for data analysis, automation, or scripting.
• Experience with business intelligence and data visualization tools (Looker, Hex, Tableau, or similar).
• Strong quantitative and analytical skills with a demonstrated ability to translate data into business insights.
• Strong communication skills and the ability to work effectively with stakeholders across different functions and levels of technical fluency.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Familiarity with cloud data platforms (e.g., Snowflake, BigQuery, Databricks).
• Familiarity with dbt for data modeling and transformation.
• Exposure to data pipeline orchestration tools (e.g., Airflow).
• Experience in fintech, financial services, or payments.
• Comfort operating in a fast-paced, high-growth environment with evolving priorities.

Compensation

The expected salary range for this role is $93,600 - $117,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

🚀SR SOFTWARE ENGINEER WANTED - DRIVE MEANINGFUL IMPACT AT HYPERGROWTH VENTURE🚀

Are you driven by impact, ownership, and a passion for elegant yet efficient systems?

⚙️What You’ll Do⚙️

• Build responsive frontend applications for complex ad operations workflows
• Deploy and maintain production cloud infrastructure (AWS/GCP/Azure) with CI/CD, monitoring, and scaling
• Collaborate on system architecture decisions supporting multiple AI agent integrations

🎮Technical Requirements🎮

Must-Have:

• Languages: JavaScript expertise with modern frameworks (React/Vue/Angular), Python expertise, and experience with at least one low-level language (C, C++, Rust, Zig, or similar)
• Experience: Building large-scale SaaS platforms from scratch; Cloud deployment and DevOps

Preferred Technologies:

• React/Next.js/Vue.js, FastAPI/Django/Flask, Docker/Kubernetes, PostgreSQL/MongoDB/Redis, Temporal/Airflow/Dagster), Kafka/RabbitMQ, AuthN and AuthZ

🧬Who You Are🧬

A driven overachiever with an owner mindset.

You're not just a coder - you're an architect who sees the big picture while mastering the details. You take pride in building high-quality systems that deliver results. You push yourself to solve problems others can't and constantly seek to expand your technical horizons.

💵Comp & Benefits 💵

Salary: 

$120-180k Base depending on experience

• Performance Bonus Eligible

Benefits include:

• Health, Dental, Vision coverage
• Unlimited PTO
• 401k + matching 
• Life Insurance
• Parental Leave
• And more ✨

🛸Why Join Us🛸

We're experiencing exceptional growth in a contracting market. We combine startup agility with established financial stability. You'll work on exciting challenges with a brilliant team of like-minded professionals who value both technical excellence and creative problem-solving. You'll have immediate impact on critical systems and clear paths for professional advancement.

This isn't just another job - it's your chance to build something meaningful with people who are as passionate and talented as you are.

🧩If this sounds like you - we’d love to talk! Apply here >>

We’re rebuilding our data foundation from the ground up - and we’re looking for a Senior Analytics Engineer who thrives at the intersection of data infrastructure, business context, and cross-functional collaboration. If you're excited by the idea of owning foundational systems that will power pricing, personalization, experimentation, and more—this role is for you. 

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA

About the Team:

As a Senior Analytics Engineer at StubHub, you’ll be a force multiplier for the entire company. You’ll build scalable data products and frameworks that empower analysts, data scientists, and business leaders to make better, faster decisions. You'll bring order to chaos, anticipate data needs before they arise, and partner with stakeholders across engineering, product, and business teams to help us unlock the full value of our data. 

What You'll Do:

• Own the development of cross-functional data models, core business metrics, and self-service dashboards/tools. 
• Build, document, and maintain robust data pipelines using tools like dbt, Airflow, Snowflake, BigQuery, or Databricks. 
• Anticipate and solve common data access patterns across product, marketing, finance, and operations teams. 
• Partner closely with data scientists, analysts, and software engineers—often serving as the bridge between product needs and data infrastructure. 
• Define and scale analytical frameworks that support experimentation, decision-making, and business health monitoring. 
• Act as a domain expert in one or more business areas (e.g., pricing, supply, demand, user growth), becoming a go-to thought partner for leadership. 
• Support real-time and batch data workflows, data governance practices, and metadata/catalog tooling. 

What You've Done:

• 5 - 10 years of experience in analytics engineering, data engineering, or business intelligence in a fast-paced, high-growth environment. 
• Expert SQL skills and strong proficiency in Python (or another programming language like Java). 
• Hands-on experience building data pipelines and models with tools like dbt, Airflow, and Snowflake (or equivalent). 
• Experience with BI tools such as Looker, Tableau, or Mode, and a strong understanding of enabling self-serve analytics. 
• Familiarity with both batch and streaming data processing patterns. 
• An ability to translate messy, real-world business problems into elegant, scalable data systems. 
• A collaborative mindset with a passion for partnering with non-technical stakeholders to unlock insights and drive impact. 
• Familiarity with data governance, observability, and metadata management tools is a plus. 

What We Offer:

• Accelerated Growth Environment: An environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale.
• Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact.
• Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to recharge as needed.
• Comprehensive Benefits Package: Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options.

About the Role

Join our Data Platform team at 10x Genomics to architect and implement our strategic Unified Data Platform (UDP). This pivotal role is focused on modernizing our data infrastructure, transitioning to a scalable Event-Driven Architecture (EDA), and building the foundation for next-generation AI/ML and self-service analytics.

• Lead the architecture and delivery of the Single Source of Truth (SSOT) for the 10x Intelligent Data Ecosystem.
• Apply advanced software engineering practices to data systems for scalability and reliability.
• Provide hands-on Senior Data Engineering leadership in developing scalable and maintainable ETL/ELT solutions and data systems in a cloud-native environment.
• Drive the systematic reduction of critical technical debt by retiring fragile legacy middleware (e.g., Boomi).
• Partner with engineering and business teams to enable advanced AI capabilities and democratize data access via Natural Language Querying (NLQ).

What you will be doing

• Architect and implement the canonical data layer and Event-Driven Architecture (EDA) using technologies like Apache Iceberg and Kafka to decouple applications and ensure real-time data flow.
• Design, build, and optimize high-volume, code-first data pipelines (real-time and batch) across a large application landscape (e.g., Salesforce, Oracle, Workday).
• Establish Amazon S3 as the Single Source of Truth (SSOT) and govern data using principles like the Medallion Architecture (Silver and Gold layers) and schema evolution.
• Develop, test, and maintain robust and scalable ELT pipelines and data models in Snowflake, including leveraging advanced features like Snowpipes, Streams, and Stored Procedures.
• Develop the data presentation layer for self-service analytics, including the Natural Language Query (NLQ) interface integrated with Generative AI (e.g., Bedrock).
• Lead technical efforts to migrate key business domains off legacy middleware and onto the new platform, eliminating the "Integration Bottleneck".
• Define and enforce data governance, quality, and security standards across the Unified Data Platform.
• Collaborate with the Architecture Review Board (ARB) to promote modern approaches such as serverless computing and Domain-Driven Design.
• Take ownership of the full development lifecycle, from prototyping and design through deployment, monitoring, and operational excellence.

Minimum Requirements

• Bachelor’s degree in Computer Science, Information Management, or a related field, or equivalent experience.
• 5+ years of hands-on experience in software engineering focused on data platform development, distributed systems, or enterprise integrations.
• Proven experience designing and implementing highly scalable data platforms on major cloud environments (e.g., AWS, GCP, or Azure).
• Deep proficiency in one or more general-purpose programming languages (e.g., Python, Java, or similar).
• Strong foundation in computer science fundamentals, including data structures, algorithms, and system design.

Preferred Skills and Experience

• Expertise in message queues and event streaming platforms (e.g., Kafka, RabbitMQ, Pub/Sub) and implementing Event-Driven Architecture.
• Experience with building data lakes/lakehouses using open formats like Apache Iceberg on cloud storage (e.g., Amazon S3).
• Expertise in modern ELT development, data modeling for OLAP/data warehousing using tools like dbt, and advanced Snowflake features (e.g., Snowpipes, Streams, Stored Procedures).
• Familiarity with containerization (Docker, Kubernetes) and Infrastructure-as-Code (IaC) principles.
• Prior experience in migrating an organization off a traditional iPaaS platform or eliminating legacy middleware.
• Experience with Generative AI integration for data access (e.g., NLQ, feature stores).

Core Technologies

• Snowflake
• Python (or Java/Scala)
• Event Streaming (Kafka or similar)
• AWS (or other major cloud platform)
• Apache Iceberg / Amazon S3
• Advanced SQL (including stored procedures, UDFs/UDTFs)
• Modern Orchestration tools (e.g., Airflow)

PsiQuantum’s mission is to build the first useful quantum computers—machines capable of delivering the breakthroughs the field has long promised. Since our founding in 2016, our singular focus has been to build and deploy million-qubit, fault-tolerant quantum systems. 

Quantum computers harness the laws of quantum mechanics to solve problems that even the most advanced supercomputers or AI systems will never reach. Their impact will span energy, pharmaceuticals, finance, agriculture, transportation, materials, and other foundational industries. 

Our architecture and approach is based on silicon photonics. By leveraging the advanced semiconductor manufacturing industry—including partners like GlobalFoundries—we use the same high-volume processes that already produce billions of chips for telecom and consumer electronics. Photonics offers natural advantages for scale: photons don’t feel heat, are immune to electromagnetic interference, and integrate with existing cryogenic cooling and standard fiber-optic infrastructure. 

In 2024, PsiQuantum announced government-funded projects to support the build-out of our first utility-scale quantum computers in Brisbane, Australia, and Chicago, Illinois. These initiatives reflect a growing recognition that quantum computing will be strategically and economically defining—and that now is the time to scale. 

PsiQuantum also develops the algorithms and software needed to make these systems commercially valuable. Our application, software, and industry teams work directly with leading Fortune 500 companies—including Lockheed Martin, Mercedes-Benz, Boehringer Ingelheim, and Mitsubishi Chemical—to prepare quantum solutions for real-world impact. 

Quantum computing is not an extension of classical computing. It represents a fundamental shift—and a path to mastering challenges that cannot be solved any other way. The potential is enormous, and we have a clear path to make it real. 

Come join us. 

Job Summary:

Quantum computing promises to solve many important problems that could never be solved on any conventional computer. At PsiQuantum we’re building a general-purpose silicon photonic quantum computer to tackle these very problems.

PsiQuantum is looking for an experienced data platform engineer who can design, implement and maintain scalable data pipelines that extract, move and transform data across the Photonic Circuits organization. This role optimizes ETL workflows and integrates various data sources (APIs, DBs, streaming systems) and ensures data quality and observability. This role will work closely with the platforms team and the circuit designers, system engineers and validation engineers. The output will enable ease of producing analytics, scaling tape-out and providing well-structured data sets for reporting. Quantum computing requires breakthrough engineering innovations; we expect software solutions that are novel and custom while at the same time, leverage automation and other best practices from the semiconductor industry. Being a startup in an all-new engineering field, the role is expected to be highly collaborative and requires excellent technical skills to execute projects to meet milestones and technical scope.

An ideal Data Platform SW Engineer candidate combines strong SW engineering skills with deep appreciation for semiconductor and chip design EDA toolchains. They are experienced in building scalable data pipelines that ingest and transform data from simulation outputs, layout tools, verification systems, test benches, lab measurements, and manufacturing yield reports. Proficient in Python and SQL, they are comfortable working with large structured and unstructured datasets (netlists, GDS metadata, waveform data, logs) and integrating disparate systems across design, verification, and fabrication environments. They understand the importance of data integrity, traceability, and reproducibility in silicon development, and design pipelines with robust validation, versioning, and auditability. The ideal candidate collaborates effectively with circuit designers, CAD/EDA engineers, verification teams, and manufacturing operations, translating complex engineering workflows into reliable, automated data infrastructure that accelerates design iteration, improves yield analysis, and enables data-driven decision-making across the chip lifecycle.

Responsibilities:

• Key member of the software solutions team responsible for developing and deploying software for test systems, product platforms and manufacturing data management.
• Design, build, and maintain scalable data pipelines that ingest data from EDA tools, simulation frameworks, verification systems, lab equipment, and manufacturing test platforms.
• Develop robust ETL/ELT workflows to transform netlists, layout metadata, waveform data, logs, and yield data into structured, analysis-ready datasets.
• Integrate disparate engineering systems across design, verification, tapeout, and silicon validation environments.
• Ensure data integrity, traceability, and version control across the chip development lifecycle.
• Implement automated validation, monitoring, and observability for pipeline reliability and data quality.
• Optimize performance for large-scale simulation outputs and high-volume manufacturing datasets.
• Collaborate with photonic circuit designers, CAD/EDA/PDK engineers, verification teams, and silicon validation engineers to translate workflow requirements into scalable data solutions.
• Build data models and infrastructure that support yield analysis, failure analysis, PPA (power, performance, area) tracking, and design iteration metrics.
• Maintain secure and compliant data handling practices across on-prem and cloud environments.
• Contribute to internal tooling and automation frameworks to reduce manual data handling and accelerate design cycles.

Experience/Qualifications:

• Bachelors or other advanced degrees in Computer Science or related engineering fields.
• 3+ years of experience building and maintaining production-grade data pipelines or data platforms.
• Use programming languages (Python, SQL) and tools (DataBricks, Apache Kafka, Spark, Airflow) to ensure high-quality, scalable data flow.
• Understanding of software engineering best practices (version control, CI/CD, testing, code reviews).
• Experience working in semiconductor, ASIC/SoC, or photonics design environments.
• Knowledge of HPC environments or high-throughput compute clusters.
• Preference for experience in supporting ML or advanced analytic engineering workflows.
• Experience with complex software development projects for custom test solutions, hardware interfaces, and platform level firmware/software OR experience developing complex experimental systems in the case of recent college graduates.
• Proven team player with an ability to work effectively across departments, sites, time zones.
• Excellent verbal and written communication skills with an ability to communicate effectively to a variety of audiences.
• Strong critical thinking, creative, innovative, analytical, and detail-oriented problem-solving skills.
• Proven track record of impactful results.
• Ability to work independently with limited direction.
• Demonstrated ability to lead and juggle multiple priorities and deliver against a schedule.
• Demonstrated interest in quantum computing.
• Ability to contribute to a fast-paced start-up environment.

PsiQuantum provides equal employment opportunity for all applicants and employees. PsiQuantum does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, or any other basis protected by applicable laws.

Note: PsiQuantum will only reach out to you using an official PsiQuantum email address and will never ask you for bank account information as part of the interview process. Please report any suspicious activity to recruiting@psiquantum.com.

We are not accepting unsolicited resumes from employment agencies.

About the Role

We're hiring a Senior Engineering Manager to lead Data Integrations at Mill. This role sits at the center of our B2B strategy: you'll own the systems that integrate Mill into our customers' enterprise environments — ERP systems, business applications, internal tools — so that we can combine our food waste estimates with their internal data and use AI to deliver actionable recommendations on how they can reduce waste.

You'll be hands-on technically — designing multi-tenant APIs, building integration pipelines, writing code — while also engaging directly with customers, driving technical partnerships, and managing a team of engineers. You'll use LLMs to accelerate integration development and unlock insights from customer data. This is a senior leadership role that demands genuine technical depth, hands-on ownership, and direct customer engagement.

What You'll Own

Customer System Integration. Design and build the integration layer between Mill and our B2B customers' enterprise environments — connecting to their ERP systems, business applications, and internal tools to pull operational data — purchasing, inventory, consumption patterns, and more. You'll combine that data with Mill's food waste estimates to power AI-driven recommendations that help customers reduce waste. You'll need to deeply understand how enterprise customers operate and what their systems require.

Multi-Tenant API Platform. Architect and operate enterprise-grade APIs for data exchange with customers — including RBAC, tenant isolation, webhooks, and reverse ETL pipelines. You'll own reliability, SLAs, and the developer experience for our partners.

LLM-Accelerated Development. Use large language models to accelerate how we build integrations, automate data mapping across disparate customer systems, and extract actionable insights from customer data. This is a core part of the role, not a side project.

Data Contracts & Governance. Own schema governance, API versioning, and data contracts across integration touchpoints. As we scale B2B relationships, this becomes critical.

Security & Compliance. Ensure data security across the integration layer: tenant isolation, RBAC, encryption, audit logging, and alignment with SOC 2, GDPR, and CCPA.

Customer Onboarding & Technical Partnerships. Be the senior technical face for B2B customers. Scope integration requirements, define data contracts, manage delivery timelines, and build long-term trust.

What We're Looking For

• 10+ years in data engineering, platform engineering, or integration-heavy backend roles, with 3+ years managing engineers
• Deep experience integrating with enterprise customer systems — ERP platforms, business applications, and third-party environments
• Strong background in multi-tenant API design, data pipelines, and integration architecture
• Experience integrating with multiple enterprise ERP and business systems (e.g., NetSuite, SAP, Oracle) — either through iPaaS platforms like Boomi/MuleSoft or through custom-built integration layers. You understand the data mapping, normalization, and error handling challenges that come with connecting to many different customer environments
• Hands-on experience using LLMs to accelerate development workflows, automate data mapping, or build intelligence into integration pipelines
• Strong instincts around data contracts, schema governance, versioning, and API design at scale
• Proven ability to work directly with B2B customers — scoping requirements, running onboarding, and managing technical relationships
• Comfortable context-switching between writing code, reviewing architecture, managing people, and talking to customers

Nice to Have

• Experience in food service, hospitality, retail, or other industries with high food waste relevance
• Experience with EDI transaction sets (850/855/856/810) or retail partner data exchange
• Background in hardware + software or IoT companies
• Experience with ML/CV data pipelines
• SOC 2 Type 2 compliance experience
• Familiarity with data orchestration tools (Airflow, dbt, Spark)

The estimated base salary range for this position is $245k to $270k, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.

Position: 

The Associate Director, Clinical Data Analytics and Reporting is a leader responsible for establishing and scaling a Clinical Research & Development clinical analytics function for a growing biotechnology company. This role will define the analytics strategy, operating model, and technology roadmap, including the technical implementation to enable high-quality, data-driven decision-making across Clinical Research & Development, with primary focus on oncology programs.  This is a hands-on role requiring demonstrated expertise in design, development, test and support of complete analytics & reporting system lifecycle. This leader will partner closely with Clinical Operations, Biostatistics, Data Management, Clinical Research, Regulatory, Safety and Clinical Quality Assurance to ensure proactive risk identification, operational excellence, inspection-ready execution across the portfolio. 

About You 

The successful candidate will combine deep clinical development expertise with advanced analytics, data governance, and visualization capabilities. The ideal candidate for this role should possess a proven track record of designing, implementing and supporting end-to-end data analytics solutions using current state-of-the-art technologies, and a deep knowledge of emerging trends and best practices in data analytics.  

What will you do: 

• Collaborate with Stakeholders in different areas of Clinical Development R&D organization, IT System Owners and external vendors to define and implement the clinical analytics vision, strategy and capabilities (e.g., dashboard, etc.) aligned with clinical development objectives. 
• Establish a scalable analytics operating model suitable for early stage through late phase development.
• Translate complex clinical and operational data into clear, actionable insights for executive and study teams (including predictive and prescriptive analytics to anticipate risks and optimize trial execution).
• Design, development, test and deployment of the complete end-to-end analytics solution to enable decision-grade dashboards and metrics across Clinical R&D.
• Design and implementation of datawarehouse/datalake/lakehouse including star schemas.
• Collaborate with System Owners, Business Owners and Subject Matter Experts to map sources system objects and attributes to data warehouse objects.
• Develop, test and support data pipelines for extract, transform, load (ETL) of the source system data to populate datawarehouse/datalake/lakehouse.
• Develop end user facing dashboards and analytics solutions.
• Support the operations of the IT systems landscape ensuring system uptime, ETL and other job completion as per schedule, ongoing system changes and enhancements. 

Qualifications 

• Post Graduate degree with 8+ years of experience or a Bachelor’s degree with 10+ years of experience in development and support of Clinical Operations analytics solutions.
• Demonstrated strong experience working with developing end user dashboards using solutions such as Qlik, Power BI, Shiny R/Python.
• Strong Experience developing datalake/lakehouse solutions on platforms such as Snowflake, Databricks, AWS, and Azure.
• Strong working knowledge of development and management of database technologies such as Postgres, SQLServer etc.
• Experience with development of data pipelines including ETL from source systems to datawarehouse/datalakes/lakehouse using solutions such as Apache Airflow, Fivetran, dbt etc.
• Excellent oral and written communication skills with high EQ to effectively collaborate with business cross-functional teams.
• Understanding of the clinical development lifecycle and demonstrated experience building analytics capabilities in clinical development
• Knowledge of Report/Dashboard development in Veeva R&D Vaults such Clinical, RIM, Quality, Safety is preferred.
• Knowledge of IT Computer System Validation (CSV) in a GxP environment is preferred.
• Experience with Automation and AI Agent Frameworks is preferred.
• Deep knowledge of RBQM, Quality by Design (QbD) and regulatory/operational expectations for clinical oversight is preferred. 

At Eikon, employee compensation also includes bonus and equity compensation, in addition to several generous benefit programs, including:​

• 401k plan with company matching​
• Medical (premiums covered by Eikon at 95%), dental and vision insurance (premiums covered by Eikon at 100%)​
• Mental health and wellness benefits​
• Weeklong summer and winter holiday shutdowns​
• Generous paid time off and holiday policies​
• Life/AD&D Insurance (premiums covered by Eikon at 100%) and optional supplemental employee-paid life/AD&D policies ​
• Enhanced parental leave benefit​
• Daily subsidized lunch program when on-site​

The expected salary range for this role is $191,000 to $209,000 depending on skills, competency, and the market demand for your expertise.

About the role

We are looking for both infrastructure engineers with expertise in machine learning pipelines and ML engineers that want to work beyond modeling to join the Data & ML infra group. This role will work across the entire ML lifecycle (dataset generation, training frameworks, compute, evaluation, and deployment) and work directly with modeling teams. This team is a good fit if you are excited to work on broad, ambiguous problems and develop across the entire ML stack. At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, closely interact with external and internal users to collect feedback, and contribute to a thoughtful, dynamic team culture.

At Applied Intuition, you will:

• Design and implement distributed cloud GPU training approaches for deep learning model training and evaluation
• Build end-to-end machine learning pipelines and integrate them into core product workflows
• Encourage change, especially in support of ML engineering best practices, and maintain a high standard of excellence
• Collaborate with engineers across the entire company to solve complex data problems at scale

We're looking for someone who has:

• A Bachelor's degree in Computer Science, Software Engineering, or equivalent
• 3+ years of professional experience
• Experience with building software components to address production, full-stack machine learning challenges. This is not purely a research problem
• Opinions about building a company-wide platform for ML training, evaluation, and deployment
• Knowledge of the open source landscape with judgment on when to choose open source versus build in-house
• Excellent analytical and problem-solving skills

Nice to have:

• Experience with developing, running, and managing orchestration systems like Airflow and Flyte that non engineers can use to build data pipelines.
• Experience with ML modeling frameworks (PyTorch, Tensorflow, etc.), and model serving platforms  (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $153,000 - $222,000 USD annually. 

About the role

At Applied Intuition, you will:

• Build and maintain large-scale data processing pipelines (ETL) for ingesting and curating driving datasets.
• Design and implement systems that automate data selection, labeling, training, and testing loops.
• Collaborate with modeling teams to improve training efficiency and model performance across iterations.
• Develop the core infrastructure that closes the loop between real-world test results and new model deployments.
• Use your engineering expertise to help Applied Intuition’s vehicles learn from data at scale, improving safety and performance.
• Mentor junior engineers and contribute to defining best practices for data-centric development.

We're looking for someone who has:

• Bachelor's or higher degree in Engineering such as Computer Science, Electrical Engineering, Software Engineering
• 3–5 years of experience in software or data infrastructure engineering.
• Expertise in building and scaling data pipelines, distributed systems, or ML infrastructure.
• Proficiency in Python and strong knowledge of data frameworks (Spark, Airflow, Kafka, etc.).
• Experience working with large-scale datasets and understanding data-driven development cycles.
• Familiarity with machine learning workflows or model training/deployment, especially automation of those processes.
• Strong systems thinking and ability to work across multiple parts of the stack (data, infra, and ML).
• Interest in seeing the direct impact of your infrastructure work on how vehicles perform and improve.

Nice to have:

• Experience with automotive (AV) or robotics systems.
• Previous work on ML platforms for large-scale products (e.g., Ads, Recommendation, or Autonomy pipelines).
• Experience with highly automated ML training workflows.
• Prior contributions to systems that connect data-driven model iteration loops (“data flywheel”).
• Ability to move fast, learn quickly, and mentor others while growing with the team.

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $125,000 - $222,000 USD annually.