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

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.

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.

Role

We’re seeking a Senior Data Analyst specializing in product analytics to help shape the future of our revenue cycle management platform. In this highly cross-functional role, you'll collaborate with product managers, engineers, and business stakeholders to gauge opportunities, guide strategy, and inform decisions with data. You’ll explore new datasets, build prototypes, monitor performance, and measure the product impact. This role offers a unique chance to take a leading role in delivering on an ambitious product roadmap using data to enhance the operational efficiency of healthcare providers.

**This role is fully remote within the US**

What You'll Do

• Partner with product managers and engineers to translate business goals into analytical requirements, perform exploratory analyses, and clearly communicate findings to support strategic decisions
• Design experiments to answer business questions, including defining key metrics and applying appropriate statistical techniques to analyze results
• Prototype analytics solutions and data products to accelerate product development
• Translate analytical findings into compelling data stories through clear visualizations that help stakeholders quickly grasp trends, patterns, and implications
• Becoming an expert in our data stack: how we get the data from customers, how we normalize that data, and how internal teams and customers consume that data
• Building, maintaining, and testing data models which support reporting and analytics.
• Uphold high standards for code quality and documentation, while contributing to a culture of peer review and continuous learning

What You Bring

• 3-5+ years' experience as a data analyst or product data scientist (or, if your y-intercept is lower, evidence that your slope is super steep)
• Strong technical skills: querying data with SQL, transforming data with dbt to shorten time to insight, performing analysis with python, and communicating findings with compelling data visualizations
• Masters in statistics or other relevant fields preferred
• Ownership: Build and own features from start to finish.
• Strategic mindset: strong ability to connect analytics to business understanding and provide actionable insights.
• Scrappiness: Navigate ambiguity effectively, understanding when it’s necessary to piece solutions together on the fly, and be able to do so.
• Product focus: How can we maximize the utility and value we deliver to our end users?
• Familiarity with experiment design and statistical analysis

Nice To Haves

• Experience with health system clinical and/or revenue cycle data is preferred

Our Tech Stack

• Data Visualization: Hex and Evidence
• Analysis: Python & Data Science libraries (numpy, pandas, etc)
• Pipelines: Snowflake, dbt, airflow, git, and AWS

Compensation

$160,000 - $190,000

#LI-Remote

ABOUT THE COMPANY:

Clari + Salesloft are building the next era of enterprise revenue — one where teams make confident decisions powered by AI and real signals. By combining our scale, insights, and AI innovation, we’re building the industry’s first Predictive Revenue System, enabling humans and AI to work together to make smarter decisions and drive consistent growth.

With thousands of customers using our platforms every day, we have an unmatched view into how revenue is actually won — the Revenue Context that reveals what happens, when, and with what outcome. This gives us a unique opportunity to transform an entire category and set a new benchmark for how modern revenue teams operate.

Join us to help transform how companies around the world run revenue — and build the platform that will guide leading revenue teams into the future.

THE OPPORTUNITY:

At Clari + Salesloft, our Principal Engineer will be pivotal to our company’s success. You will be a key member of our fast-growing and high-performing Product Engineering org. We are looking for experienced Principal Engineers who can help realize Clari + Salesloft vision with their passion and proven track record of excellence and innovation. We are looking for engineers who are passionate about their work and who thrive working on leading-edge cloud-based technologies to develop ground-breaking AI-driven enterprise-grade applications.

On a day-to-day basis, you will be responsible to -

• Shape future-proof interfaces that are easy to build against and meet the requirements of client-facing teams
• Brainstorm with Product Managers, Designers and Engineers, and other cross-functional partners to conceptualize and build new features for our growing user base
• Produce high-quality results by leading large cross-functional projects that have a significant impact on the business
• Debug production issues across services and multiple levels of the stack, and uplevel the observability and reliability of the overall system
• Own architecture decisions across multiple teams, drive long term technical strategy, and raise the bar for engineering excellence company-wide
• Mentor Staff and Senior engineers 

In addition to working with amazing colleagues who exemplify our ‘team over self’ core value, you will also have the opportunity to work on impactful and revolutionary software that is changing the way sellers sell. You will have an opportunity to make a difference. 

WHAT WE’RE LOOKING FOR:

We are seeking Principal Software Engineers who would be Working on cutting-edge technologies alongside a highly motivated and skilled team eager to learn and grow together

If you’re looking for an opportunity to learn more, do more, and become more, then becoming a Principal Software Engineer is the career path for you!

THE TEAM:

The Engineering Team at Clari + Salesloft is deeply committed to building an enterprise-grade platform that serves as the backbone for our customer's most critical business process - Revenue. With an unrelenting commitment to innovation, our mission is to craft the ultimate revenue intelligence platform for our customers. Rooted in Agile principles, we foster a culture of adaptability and efficiency across all our teams. If you're energized by the prospect of contributing to a dynamic environment that emphasizes collaboration, continuous improvement, and leveraging the forefront of technology to address customer needs, we would love to meet you.

THE SKILL SET:

• 12+ years of experience in building distributed systems or platform infrastructure designed for high-scale, data-intensive workloads
• Expert-level proficiency in Java or a similar object-oriented language and familiarity with infrastructure tooling (Airflow, Kubernetes, Ray, Terraform), service frameworks (FastAPI, gRPC), and observability platforms (Prometheus, Grafana, DataDog, Splunk)
• Deep experience with cloud infrastructure, ideally AWS or GCP, including Kubernetes clusters (GKE/EKS), serverless architectures, and managed services (e.g., Lambda, Cloud Run, ECS)
• Architected solutions requiring distributed data infrastructure: message queues (Kafka, Kinesis), caching systems (Redis, Memcached), database optimization, and building resilient, fault-tolerant architectures
• Expertise with SQL (postgres) / NoSQL (MongoDB) and data warehouse modeling; capable of optimizing complex data queries, joins, aggregations, and transformations
• Solid improvements of platform monitoring and optimizations, including identifying performance bottlenecks, latency optimization, cost management, and scaling high-throughput API services efficiently

At Clari + Salesloft, we are committed to creating an inclusive and supportive workplace where everyone belongs and can thrive. We focus on culture add, not culture fit, and believe our teams are made stronger by the unique perspectives, experiences, and identities each person brings.

We are proud to be an Equal Opportunity Employer and provide employment opportunities to all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, pregnancy, or any other characteristic protected by law.

If you’re excited about this role even though your experience may not perfectly match every requirement, we encourage you to apply. We are actively hiring across multiple geographies and would love to welcome passionate, curious, and mission-driven individuals to our growing team. Explore our open roles and consider joining us!

#LI-Hybrid

Please note that all official communication regarding job opportunities at Clari + Salesloft will come from an @clari.com  or @ salesloft.com email address. If you receive messages on LinkedIn or other job platforms claiming to be from Clari + Salesloft, they may not be legitimate. To verify the authenticity of any job-related communication, please visit our official Careers Page.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, notetaking, or summarizing responses. These tools assist our recruitment team but do not replace human judgment — all hiring decisions are made by people. If you would like more information about how your data is processed or prefer to opt out of any AI-assisted tools, please let your recruiter know. Opting out will not impact your experience or consideration.

The Opportunity

The Sales Engineer is responsible for driving new business growth and expanding Air Equipment Company’s Controls Products presence across the commercial HVAC and building systems marketplace. This role serves as a trusted advisor to consulting engineers, mechanical contractors, controls contractors, and building owners by delivering technical expertise, responsive service, and value-added solutions. The Sales Engineer will focus specifically on AEC’s industry-leading controls and critical environment offerings, including ABB Variable Frequency Drives (VFDs) and Phoenix Controls airflow control solutions, along with complementary product lines such as airflow monitoring, dampers, hydronic measurement, demand control ventilation, and life safety systems. This position owns the sales process from opportunity development through project execution support, ensuring AEC Controls Department continues to be Kentucky’s premier manufacturer’s representative firm for HVAC technical products.  

Responsibilities

• Develop and manage strong relationships with owners, engineers, contractors, and end users across the assigned territory, with an emphasis on controls and critical environment applications.
• Identify, generate, qualify, and pursue new sales opportunities aligned with AEC’s strategic growth goals in the Controls Products market.
• Promote and support key AEC controls product lines, including but not limited to:
  • ABB Variable Frequency Drives (VFDs)
  • Phoenix Controls Venturi valves and airflow control systems
  • Tamco industrial and commercial damper solutions
  • Onicon flow and energy measurement systems
  • Antrum demand control ventilation (DCV) solutions
  • Honeywell gas detection and safety monitoring systems
• Support customers with equipment selection, system application guidance, and design assistance for complex mechanical and controls projects.
• Prepare quotations, pricing, and sales proposals in coordination with internal estimating, engineering, and operations teams.
• Deliver technical presentations and product demonstrations highlighting manufacturer capabilities, system performance, and solution value.
• Maintain accurate pipeline tracking, forecasts, and opportunity documentation within CRM systems.
• Collaborate with internal engineering, service, and project execution teams to ensure successful project delivery and long-term customer satisfaction.
• Provide ongoing customer support before and after the sale, ensuring AEC solutions perform as intended and relationships remain strong.
• Conduct business ethically, legally, and in alignment with AEC’s core values.

Competencies:

• Excellent verbal and written communication skills to effectively convey technical information and to interact effectively with customers and team members
• Strong customer service skills to address inquiries and resolve issues
• Analytical skills to diagnose and solve technical problems
• Ability to identify sales opportunities and develop relationships with potential customers
• Regular interaction with customers via phone, email, and video conferencing
• Strong technical aptitude and ability to understand complex engineering concepts
• Ability to work independently as well as part of a team
• Strong attention to detail
• Ability to work in a fast-paced environment

The Ideal Profile

• Bachelor’s degree in Engineering, preferably in Mechanical, Electrical, or Industrial Engineering
• Minimum 3 years of HVAC Sales experience
• Knowledgeable regarding ASHRAE recommendations, HVAC industry
• Strong mathematics and physics understanding
• Education and experience with the construction and engineering industry, with specific experience in dealing with construction drawings, specifications, construction schedule and processes is a plus.

Physical Demands

While performing the duties of this job, the employee is regularly required to use hands to operate computer keyboard and telephone, reach with hands and arms. The employee frequently is required to stand, walk, and sit. The employee is occasionally required to climb or balance and stoop, kneel, crouch, or crawl. The employee must regularly lift and/or move up to 25 pounds. Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception, and ability to adjust focus.

About the Role

iCapital is looking to hire an experienced Python Developer with expertise in web scraping, automated portal interactions, and cloud-native deployment using AWS. The ideal candidate will have hands-on experience working with Playwright for browser automation, managing multi-factor authentication (MFA) flows, and deploying scalable scraping tasks via AWS Lambda and related services. This role will assist in architecting and building robust, secure, and scalable scraping solutions that interact with complex web applications and secured portals.

Responsibilities

• Assist with the design and implementation of advanced scraping solutions using Python, Playwright, and AWS services.
• Automate interactions with JavaScript-heavy and authentication-secured websites, including handling MFA, CAPTCHAs, and session or token-based login flows.
• Architect scraping pipelines using serverless AWS components such as Lambda, Step Functions, S3, CloudWatch, and Secrets Manager.
• Build systems that scale to support high volumes of data extraction with fault tolerance, retries, and intelligent logging.
• Integrate and manage complex workflows across multiple portals, APIs, and data sources.
• Contribute to architectural decisions, tooling, and best practices.

Qualifications

• Bachelor’s or master’s degree in computer science, software engineering, or related field, or equivalent professional experience
• 10+ years of experience in Python development, with a strong focus on automation and data extraction
• Proven expertise in web scraping using tools like Playwright, Selenium, Scrapy, BeautifulSoup, and requests
• In-depth experience handling multi-step authentication flows, including multi-factor authentication (MFA), CAPTCHA solving, and session or cookie management
• Proficient in deploying and managing scraping workloads in AWS, particularly Lambda, S3, IAM, CloudWatch, and Secrets Manager
• Experience with asynchronous programming, headless browsers, and JavaScript-rendered content
• Solid understanding of web protocols (i.e. HTTP, HTTPS, cookies, headers), and the ability to reverse-engineer network calls and authentication mechanisms
• Comfortable working with APIs, JSON/XML, and data transformation
• Experience with CI or CD pipelines, Docker, and infrastructure as code (i.e. CloudFormation, Terraform)
• Familiar with data pipeline orchestration tools such as Apache Airflow or AWS Step Functions
• Prior experience scraping from secure or enterprise-level portals (i.e. financial, healthcare, legal)
• Background in data engineering or ETL workflows is a plus
• Exposure to Python testing frameworks and writing unit or integration tests

Benefits

The base salary range for this role is $130,000 to $160,000.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).

We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.

For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us  Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/

iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

This position does not offer visa sponsorship now or in the future.

iCapital is seeking an exceptional Data Engineer to help scale the data foundations that power the business. This individual will design, build, and optimize the data pipelines and infrastructure that enable data to be a strategic asset across the organization. This role is highly collaborative and will partner with the Product, Engineering, Analytics teams and business stakeholders to quickly understand evolving challenges and deliver scalable, maintainable, and high‑quality solutions.

Data sits at the core of iCapital’s operations. The firm relies on clean, reliable, well‑structured data to drive decision‑making, enhance client experiences, and support a rapidly growing product suite. This individual will be responsible for moving and transforming data and developing a deep understanding of the business context behind it and help teams act on insights.

Responsibilities

• Develop and automate large scale, high-performance data platform pipelines and infrastructure to drive iCapital business growth and enable data-driven decision making.
• Design and develop reusable components and frameworks for ingestion, cleansing, and data quality.
• Streamline the ingestion of raw data from various sources into our Data Lake and Data Warehouse.
• Design data models for optimal storage and retrieval that represent the tangible business domains across iCapital’s ecosystem.
• Coordinate closely with the Operations, Sales, and Product Development teams daily to push iCapital’s FinTech strategy and improve the overall profitability of the business.

Qualifications

• 6-10 years of professional experience in a data engineering or data-driven software engineering role
• Exceptional Python and SQL skills
• Extensive experience with orchestration frameworks (Prefect, Airflow, Dagster, etc.)
• Deep understanding of OLAP (Snowflake, Databricks) and OLTP (PostgreSQL, MongoDB) databases and ELT frameworks (dbt, dlthub)
• Experience developing and deploying code to Cloud environments (AWS, GCP, Azure)
• Possess a strong grasp of object-oriented and functional programming and an ability to write easy-to-scale, high-quality code
• Experience leveraging stream processing frameworks (Kafka, Flink, Spark)
• Knowledge of infrastructure-as-code frameworks (terraform or cloud formation)
• Detail-oriented and able to multitask and work in a fast-paced environment
• Able to work independently while also being a strong team player
• Excellent written and verbal communication
• Passionate about learning and mastering cutting-edge technologies
• Professional experience with JVM based languages such as Scala, Java, and Kotlin is preferred
• Knowledge of financial markets and financial instruments is preferred

Benefits

The base salary range for this role is $100,000 to $135,000.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).

We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.

For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us  Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/

iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

About the Role

The Senior Support Engineer role is a key member of the post-sales team working closely with engineering, sales, customer success, and directly with customers. This person is a technical expert able to assess and resolve setup issues, bugs, or any other technical challenges customers may face (e.g. scripting challenges, data exports). This role is a crucial part of the customer satisfaction function on the team. The ideal person loves to figure out why something is not working and can clearly articulate the best way to resolve – sometimes creatively.

We’re a remote-first company with team members in San Francisco, Los Angeles, New York, and more. 

Your Impact

• Act as the first line of support for technical issues raised via support tickets, Slack channels, or through Customer Success Managers, communicating clearly and effectively with both technical and non-technical stakeholders throughout the resolution process.
• Work directly with customers to integrate Northbeam into their ecommerce and analytics infrastructure, or to assess and resolve issues when troubleshooting is required.
• Diagnose and resolve technical issues by analyzing customer implementations, including scripts such as Pixels and Orders APIs.
• Own data quality issues end-to-end, partnering with internal teams to address proactively flagged issues and working with customers to resolve them.
• Escalate complex or product-level issues to Engineering when appropriate, providing clear context and reproduction details.
• Continuously improve external-facing documentation to enable smoother onboarding and more self-serve customer workflows.

Role Characteristics

• Approximately 70–80% of the role is backend-focused, involving debugging data pipelines and investigating logs.
• The role usually works closely with the data and engineering teams, rather than the product teams.
• Success in this role requires strong analytical thinking, attention to detail, and comfort working through ambiguous technical problems.

What You Bring

Experience

• Bachelor's Degree or similar experience preferred, but not required
• 2+ years of software engineering or support engineering experience
• You should be proficient with:
• Writing and editing SQL queries 
• JavaScript and HTML (basics)
• Web based APIs
• 2+ years of experience working directly with customers in a technical or support capacity.
• Strong ability to translate technical concepts into clear, easy-to-follow documentation, emails, and instructions.
• Excellent written and verbal communication skills.

Technical Skills

• Administrator tooling:
• Retool, ActiveAdmin, Django Admin, or other similar tools
• Python (nice to have)
• Proficient in data analytics tools (nice to have)
• Working knowledge of APIs, Datadog, Airflow, Postgres, and BigQuery.

#LI-Remote

About the Role

The Support Engineer role is a key member of the post-sales team working closely with engineering, sales, customer success, and directly with customers. This person is a technical expert able to assess and resolve setup issues, bugs, or any other technical challenges customers may face (e.g. scripting challenges, data exports). This role is a crucial part of the customer satisfaction function on the team. The ideal person loves to figure out why something is not working and can clearly articulate the best way to resolve – sometimes creatively.

We’re a remote-first company with team members in San Francisco, Los Angeles, New York, and more. 

Your Impact

• Act as the first line of support for technical issues raised via support tickets, Slack channels, or through Customer Success Managers, communicating clearly and effectively with both technical and non-technical stakeholders throughout the resolution process.
• Work directly with customers to integrate Northbeam into their ecommerce and analytics infrastructure, or to assess and resolve issues when troubleshooting is required.
• Diagnose and resolve technical issues by analyzing customer implementations, including scripts such as Pixels and Orders APIs.
• Own data quality issues end-to-end, partnering with internal teams to address proactively flagged issues and working with customers to resolve them.
• Escalate complex or product-level issues to Engineering when appropriate, providing clear context and reproduction details.
• Continuously improve external-facing documentation to enable smoother onboarding and more self-serve customer workflows.

Role Characteristics

• Approximately 70–80% of the role is backend-focused, involving debugging data pipelines and investigating logs.
• The role usually works closely with the data and engineering teams, rather than the product teams.
• Success in this role requires strong analytical thinking, attention to detail, and comfort working through ambiguous technical problems.

What You Bring

Experience

• Bachelor's Degree or similar experience preferred, but not required
• 2+ years of software engineering or support engineering experience
• You should be proficient with:
• Writing and editing SQL queries 
• JavaScript and HTML (basics)
• Web based APIs
• 2+ years of experience working directly with customers in a technical or support capacity.
• Strong ability to translate technical concepts into clear, easy-to-follow documentation, emails, and instructions.
• Excellent written and verbal communication skills.

Technical Skills

• Administrator tooling:
• Retool, ActiveAdmin, Django Admin, or other similar tools
• Python (nice to have)
• Proficient in data analytics tools (nice to have)
• Working knowledge of APIs, Datadog, Airflow, Postgres, and BigQuery.

#LI-Remote

The role:

As a Staff Full Stack Engineer, you will serve as a cornerstone of technical leadership, driving the ideation, architectural design, and optimization of enterprise-scale, full-stack ecosystems. We are seeking a visionary with 8+ years of engineering depth and a proven track record of delivering complex, end-to-end solutions. In this role, you will bridge the gap between high-level business strategy and technical execution, championing engineering excellence while serving as a pivotal mentor and subject matter expert to the broader engineering organization.

What you’ll do: 

Engineering & AI Architecture

• Architectural Leadership: Architect and deploy sophisticated, end-to-end applications, leveraging deep expertise in interactive interfaces and complex data integration—including the orchestration of AI-native database functions like Snowflake Cortex.
• Agentic AI Integration: Partner with AI specialists to architect multi-agentic systems, implementing autonomous, stateful workflows designed to solve high-consequence, real-world business challenges.
• Data Orchestration: Design and automate high-performance real-time and batch data pipelines using enterprise orchestration tools such as Apache Airflow, ensuring seamless data liquidity across the stack.

DevOps & Operational Excellence

• Infrastructure as Code (IaC): Standardize deployment lifecycles and cloud infrastructure by implementing GitOps methodologies via ArgoCD, GitLab CI/CD, and AWS best practices.
• Workflow Optimization: Deploy and tune complex business process engines within enterprise frameworks, ensuring maximum reliability, scalability, and observability.

Product Ownership & Strategy

• Technical Decomposition: Lead the translation of ambiguous product requirements into rigorous technical specifications, overseeing the entire execution lifecycle from initial ideation to post-deployment optimization.
• Strategic Collaboration: Act as a technical bridge between Product, Design, and Engineering to deliver member-centric solutions while fostering a culture of continuous learning and growth.

Governance & Innovation

• Technical Stewardship: Drive engineering rigor through comprehensive code and design reviews, serving as a final decision-maker for critical architectural choices and software standards.
• Innovation Advocacy: Maintain a cutting-edge pulse on GenAI, LLM infrastructure, and emerging tooling; proactively translating industry trends into actionable product roadmaps and enhanced technical capabilities.

What you’ll need:

Education & Experience

• Academic Foundation: Bachelor’s or Master’s degree in Computer Science, Engineering, or a strictly related technical discipline.
• Professional Tenure: 8+ years of robust software engineering experience, with a specialized focus on architecting full-stack AI-driven product ecosystems.
• Proven Reliability: A distinguished track record of delivering production-grade, highly available cloud services that operate reliably at enterprise scale.

Technical Mastery

• Full-Stack Command: Advanced proficiency in the React and Node.js ecosystems, with a mastery of seamless front-to-back-end integration for bespoke enterprise applications.
• Data & AI Infrastructure: Extensive hands-on experience with modern database platforms—Snowflake preferred—including the utilization of Snowflake Cortex and advanced AI/ML integration patterns.
• Pipeline Orchestration: Deep expertise in designing and managing complex real-time and scheduled data pipelines using Apache Airflow.
• DevOps & GitOps: Comprehensive experience in Infrastructure as Code (IaC) and environment management, utilizing ArgoCD and GitLab CI/CD to drive automated, resilient deployment strategies.

Leadership & Influence

• Strategic Mentorship: Committed to the growth of the engineering organization through active mentorship, fostering a high-performance culture, and elevating the technical caliber of the team.
• Operational Excellence: A relentless advocate for engineering rigor, consistently challenging the status quo to drive continuous improvement in code quality and architectural standards.
• Cross-Functional Diplomacy: Exceptional communication skills with the ability to bridge technical and non-technical domains, driving consensus and decision-making among diverse stakeholders.
• Organizational Catalyst: A proactive leader who takes end-to-end ownership, champions a culture of innovation, and builds influential partnerships across the broader engineering community.

Nice to have:

• Advanced AI & LLM Implementation: Direct experience deploying and scaling production-level Generative AI solutions, specifically LLM-powered agents or Retrieval-Augmented Generation (RAG) architectures.
• Sector Expertise: Previous background in Fintech or high-throughput consumer-facing environments, with an understanding of the unique security and regulatory nuances involved.
• Cloud Proficiency: Advanced experience with AWS ecosystem services and a broad familiarity with modern cloud-native orchestration platforms.
• Architectural Rigor: A sophisticated understanding of latency, throughput, and scalability trade-offs, with the ability to optimize complex distributed systems for performance.
• Computer Science Depth: Strong conceptual mastery of diverse programming paradigms, including Object-Oriented (OOP) and Functional Programming, to ensure clean, maintainable, and modular codebases.
• Evolving AI Ecosystems: Experience navigating and integrating emerging AI workflow orchestration tools and third-party AI research platforms.

The role:

As a Senior Full Stack Engineer, you will serve as a primary contributor in the development, deployment, and optimization of enterprise-grade, full-stack custom applications at scale. The ideal candidate brings 5+ years of robust engineering experience, a distinguished history of end-to-end delivery, and comprehensive mastery of software design—ranging from intricate user interfaces and business workflows to foundational back-end data architecture. You will collaborate with cross-functional teams to define technical strategy, advocate for engineering excellence, and deliver high-impact solutions directly to our member community.

What you’ll do: 

• Architect, design, and build end-to-end user-facing software applications using rich interactive user-interfaces with your expertise working with information extracted from databases and APIs (including leveraging native database functions such as Snowflake Cortex for advanced AI workloads).
• Manage deployment pipelines and infrastructure as code using ArgoCD, GitLab CI/CD, and AWS best practices.
• Collaborate with the AI engineers on the team to implement multi-agentic AI applications, enabling autonomous, stateful, and collaborative agent workflows for complex, real-world problem solving
• Own technical decompositions of new product requirements; lead delivery from ideation to deployment and continual improvement.
• Deploy, optimize, and monitor complex business process workflows on enterprise frameworks 
• Automate real-time and batch data flows using orchestration tools such as Apache Airflow.
• Participate in code and design reviews, and make technical decisions for design and architecture of software solutions.
• Collaborate with Product, Design, and Engineering to deliver high-impact solutions and foster a growth-mindset environment.
• Stay current with the latest trends in software engineering, GenAI, LLM infrastructure, and the evolving tooling ecosystem; generate ideas to expand product capabilities and technical reach.

What you’ll need:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• 5+ years of professional software engineering experience, with a focus on full-stack frameworks and engineering to develop custom product delivery specializing in AI
• Solid devops and infrastructure-as-code experience using ArgoCD and GitLab for deployment, CI/CD, and environment management.
• Advanced proficiency in React, Node.js, and front-end–to–back-end custom app development.
• Extensive hands-on experience with database platforms - Snowflake strongly preferred, including advanced features, AI/ML integrations, and Snowflake Cortex.
• Deep expertise in orchestrating real-time and scheduled pipelines with Airflow.
• Track record of delivering high-quality, production-grade, scalable, and highly available cloud-based services.
• Strong communicator; able to collaborate and drive decision-making with cross-functional stakeholders.
• Willingness to take ownership, and champion learning and innovation within the organization.

Nice to have:

• Exposure to other cloud-native or AI workflow orchestration platforms.
• Experience with AWS
• Prior fintech or high-throughput consumer product experience.
• Experience deploying and scaling LLM-powered chatbots or retrieval-augmented generation (RAG) platforms.

What we offer:

• Competitive compensation package including equity and annual bonuses
• Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and  MetLife (including a medical plan with infertility benefits)
• MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance
• Flexible PTO, 10 paid holidays, and generous parental leave policies
• Our office is centrally located in Mountain View, CA
• Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
• Long Term Disability, Short Term Disability, Life Insurance
• Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation) 
• Fidelity 401(k)
• Commuter, FSA, Dependent Care FSA, HSA
• Various incentive programs (referral bonuses, patent bonuses, etc.)

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.

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

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

Position Overview

Woolpert is hiring a Senior Software Engineer to join our dynamic Atlas Labs team supporting our Geospatial sector. This position reports to the Director of Product and AI. Atlas Labs oversees technology development for Woolpert’s Geospatial sector, including various types of AI model development, R&D, software infrastructure, and user-facing products.

We are unable to provide visa sponsorship for this position.  Applicants must already possess work authorization in the country the job is located.

What You Will Do:

• Contribute to the planning, research, design, architecture, development, and testing of Atlas Labs software features. You’ll write code daily, definitely in Python and possibly in C++ or JavaScript.
• Work as part of a cross-functional Scrum team with domain experts in AI/ML, Geospatial Data, Software Engineering, and GIS.
• Collaborate with internal and external users to ensure the correctness, quality, and availability of Atlas Labs software products.

What You Will Bring:

• Meaningful employment experience working on commercial software products
• Experience writing production code in Python, preferably dealing with large datasets
• Demonstrated experience or academic output in a relevant domain:
• Geospatial Data Processing
• Computer Vision
• AI & Machine Learning
• LiDAR
• Robotics/Self-Driving/Autonomy
• General familiarity with relevant technologies:
• Linux, Docker, and GitHub
• AI/ML frameworks (Tensorflow, Pytorch)
• Cloud platforms (Azure, AWS, Google)

Nice to Have:

• Familiarity with GIS applications like ESRI, QGIS, Google Earth
• Familiarity with orchestration frameworks like Kubernetes, AirFlow, MLFlow
• Programming experience in C++ or JavaScript
• Experience with Agile processes like Scrum

Benefits You Will Love

Certified as a Great Place to Work, Woolpert is one of the fastest-growing architecture, engineering, and geospatial companies in the world. With over 75 offices and countless projects around the globe, you’ll work on meaningful assignments that improve quality of life around the world. In addition to offering competitive pay, we provide employees with a robust set of unique benefits, including:

• Freedom to Work program: Set your own schedule and location (as appropriate).
• Principal program: Earn the opportunity to become an owner of the firm.
• Flexible paid time off/vacation: Take time off when it makes sense for you and your team.
• Career development: Explore a wide range of learning and growth opportunities within and across industries.
• Health, life, vision, and dental insurance: Cover all your medical bases.
• Paid sick time, retirement plan, fitness reimbursement, pet insurance, identity protection, technology stipend, employee assistance program, and more!

#LI-Hybrid

Position Overview:

We’re looking for a Senior Data Implementation Engineer to help lead and accelerate Acadian’s data transformation efforts. This role is central to reimagining and rebuilding our data platform so that we can continue to scale our investment research, production data workflows, and operational capabilities in a rapidly evolving landscape.

You’ll be hands-on in designing and implementing modern data pipelines and platform capabilities using tools such as Apache Arrow, Polars, Dagster, and other emerging technologies. You’ll also help shape how we use AI-assisted development tools, such as Claude & ChatGPT, and related automation approaches, to improve the speed, quality, and maintainability of data pipeline development.

This is a senior engineering role for someone who can operate across both strategy and execution: deeply understanding existing systems, designing pragmatic transition paths, mentoring others, and building reliable, scalable, high-performance data infrastructure that directly supports Acadian’s quantitative investment process.

Acadian supports a hybrid work environment; employees are on-site in the Boston office 3 days a week.

What You’ll Do

• Lead Data Pipeline Design and Implementation
  • Design, build, and optimize robust data pipelines that are reliable, scalable, observable, and performant. Use modern data engineering tools and patterns to support investment research, production workflows, and downstream analytics.
• Drive System Modernization
  • Deeply understand existing data systems, identify architectural limitations, and lead the transition toward more modern, maintainable, and efficient data architectures.
• Shape Technical Direction
  • Partner with Data Platform Engineering, Data Analysis, and investment teams to define implementation patterns, pipeline standards, and architectural approaches that can scale across the organization.
• Apply AI Tooling to Engineering Workflows
  • Use AI-assisted development tools such as Claude, ChatGPT, or similar technologies to accelerate pipeline development, automate repetitive workflows, improve documentation, generate tests, and enhance developer productivity.
• Mentor and Lead Others
  • Provide technical guidance to junior and mid-level engineers. Help raise the engineering bar through code reviews, design discussions, pairing, documentation, and thoughtful mentorship. Lead small project teams or workstreams when needed.
• Improve Reliability and Operational Excellence
  • Develop systems with strong testing, monitoring, lineage, data quality checks, and operational supportability. Help ensure that data pipelines are resilient, transparent, and easy to maintain.
• Collaborate Across Teams
  • Work closely with stakeholders across technology, data, research, and investment teams to understand requirements, resolve ambiguity, and deliver solutions that create measurable business value.
• Continuously Improve the Platform
  • Identify opportunities to simplify, automate, and improve the data ecosystem. Champion practical innovation while balancing speed, stability, maintainability, and long-term architectural quality.

We’re Looking for Teammates With

• Bachelor’s degree in a relevant field

• A strong background in data engineering, data platform implementation, or data-intensive software engineering, ideally with 5+ years of experience in a financial, investment, or technology-driven environment.
• Deep experience building production-grade data pipelines, including ingestion, transformation, validation, orchestration, monitoring, and deployment.
• Strong Python programming skills, with relevant experience working with Dagster, Airflow or similar technologies.
• Experience with modern data architecture patterns such as data lakehouse, Medallion architecture, composable data systems, microservices, and event-driven or workflow-oriented architectures.
• Familiarity with Data Mesh concepts, including decentralized data ownership, domain-oriented data products, governance, and discoverability.
• Experience with orchestration, workflow, and data transformation tools such as dbt, Polars, Pandas, Apache Arrow, or comparable technologies.
• Practical experience using AI-assisted development tools such as Claude, ChatGPT, GitHub Copilot, or similar platforms to support data pipeline development, automation, testing, documentation, and engineering productivity.
• Demonstrated ability to mentor engineers, lead technical workstreams, and influence engineering practices across a team.
• A strong sense of ownership and the ability to operate effectively in ambiguous environments, balancing tactical delivery with long-term architectural thinking.
• A passion for building systems that are efficient, scalable, reliable, observable, and easy for others to use.
• An understanding of how data infrastructure supports the broader investment process, and a desire to deliver solutions that improve outcomes for clients and create meaningful business impact.

The base salary range for this role is $175,000 – $200,000 per year. Actual compensation will be determined based on a candidate’s skills, qualifications, and relevant experience. In addition to base pay, this position may be eligible for discretionary incentive compensation and includes participation in Acadian’s comprehensive benefits program, which includes health, retirement, and wellness offerings.

 About the Role:  

At Evio, we are building a suite of solutions that enable pharmacy innovation and improved patient outcomes. Our solutions infrastructure is foundational to the value we offer to customers.  We are seeking an experienced Data Engineer who wants to build reliable, scalable systems to bring our mission to life.   

In this role, you will design, develop, and maintain our AWS-cloud-native data platform and systems necessary for efficient data processing, storage, and analysis. This role will work closely with our product management and data analytics teams to create and manage effective data ETL processes on our platforms: helping shape how data flows across our ecosystem and ensuring it is secure, accurate, and trustworthy.  

This is a hands-on role for a team player who wants to build a best-in-class system and make a difference in health care. We are a lean team with strong company culture, and every teammate plays a mission-critical role in our success.  

Key Responsibilities: 

Design and administer data systems:  

• Implement cloud-native data solutions across cloud services such as AWS Glue, AWS Lambda, AWS Step Functions, Redshift, Aurora, Amazon S3, MWAA-Airflow.
• Design and implement scalable data architectures using AWS cloud services, including data lakes, data warehouses, bulk data ingestion, and transaction processing.  
• Collaborate with customers and teammates to comprehend data requirements and translate business needs into well-designed data models.  
• Assemble large, complex data sets that meet functional business requirements.   
• Stay current with AWS services and recommend suitable tools for specific data engineering tasks.  
• Develop and support the internal applications using Python, SQL, and Stored Procedures.  

Build reliable data processes:  

• Develop, implement, and maintain ETL processes to ingest, clean, and transform complex health care data into our application data platforms.  
• Automate manual processes and to optimize data delivery and reduce operational friction. 

Optimize data pipeline performance:  

• Monitor and tune data pipelines and data storage for performance, cost, and reliability.  
• Implement caching mechanisms and data partitioning strategies to enhance query efficiency and reduce data processing times.  
• Continuously evaluate tools and recommend improvements, striving to consistently raise the bar.  

Lead and collaborate company-wide:  

• Provide technical guidance and mentorship within the data engineering team and foster a collaborative and innovative environment.
• Partner closely with product and analytics team to understand business goals and engineer solutions to the right problems.   
• Contribute to a culture of transparency, accountability, and continuous improvement.  

Protect and govern data responsibly:  

• Implement and enforce data security measures and maintain data governance standards and access controls to protect sensitive data.
• Ensure compliance with health care data regulations and industry best practices.  

The skills and experience you bring to this role include:    

• Bachelor’s degree in computer science, Informatics, Information Systems, or another quantitative field. 
• 10+ years of experience in data engineering or a similar role with demonstrated technical leadership experience.  
• Expertise building and administering, including writing views, stored procedures, and triggers, in AWS-native data systems (Redshift, Aurora, RDS PostgreSQL, Glue, Lambda, Step Functions, MWAA-Airflow).
• Strong Python and SQL experience, including advanced query design and database optimization.
• Experience with healthcare data (Medical Claims, Rx Claims) or similar healthcare data is required.  
• Ability to develop subject-matter expertise and partner thoughtfully with business teams.
• Trusted partner: reliable to deliver accurate work in a timely manner. 
• A passion for working with a team to improve how data drives meaningful outcomes.  

Salary Considerations: 

Anticipated annual base pay range: $130,000 - $150,000 plus additional variable compensation based on performance.

At Evio, we’re committed to building a competitive compensation package to honor the value our teammates bring as well as attract and retain top talent that is aligned with our culture, mission and values. Compensation includes base pay (range shown) and could include other variable compensation opportunities depending on job seniority, location, and date of hire. Evio also offers a number of attractive benefits to eligible teammates including health insurance, retirement savings, life and disability insurance, paid and unpaid time off, and other benefits to make sure Evio teammates and families are well supported.  

Please note that the base pay information shown is a general guideline for the job responsibilities and qualifications listed. Salary decisions are based on candidate experience, and market and business considerations. 

  Evio Benefits:

• Great Health Insurance
  The company pays 100% of medical, dental, and vision premiums for teammates, and 50% for dependents.
• 401K Match
  Evio matches 100% of teammate contribution up to 5% of salary, subject to IRS limits. 
• Time Off
  We have a flexible vacation policy for teammates to unplug and recharge when you need it. There is no minimum or maximum amount of vacation allowed per year, and there is no payment in consideration for unused vacation. Vacation is to be used at your discretion, with approval of leadership.
• Parental Leave
  Generous paid leave for new parents (includes birth and non-birth parents).

Evio values a diverse workplace and is committed to supporting and celebrating the diversity that each teammate brings to the table. We are proud to provide equal employment opportunities to all teammates and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, medical condition, genetic information, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.  

About the Role
Our Platform Infrastructure team is the backbone of everything we do at Attentive, providing a resilient and cost-effective platform that seamlessly handles billions of events from over 100 million customers daily. We own everything from compute, persistence, and networking to observability and deployments. Joining our team offers a high-growth career opportunity to collaborate with some of the world’s most talented engineers in a high-performance, high-impact culture.

What You’ll Accomplish

• Spearhead FinOps initiatives to increase cost transparency and optimize resource utilization across teams
• Provide guidance and mentorship to engineers on cost-optimization best practices
• Collaborate with teams across the organization to implement cost-saving measures
• Analyze, troubleshoot, coordinate, and resolve complex infrastructure issues
• Proactively lead infrastructure initiatives that have a company-wide impact
• Partner with engineering teams to influence cost-effective architectural and design choices
• Develop automation workflows to enhance team productivity and efficiency
• Foster a culture of continuous improvement by encouraging innovative thinking and challenging established norms

Your Expertise

• Bachelor's degree in Computer Science, Engineering, or related field; Master’s degree preferred
• 2+ years of experience in FinOps or cloud cost management
• 5+ years of experience in cloud infrastructure management, development or related roles
• Proficiency in some of the following technologies: AWS, Datadog, Kubernetes, Vantage, Terraform, Java
• Strong analytical and problem-solving skills with a keen attention to detail
• Excellent communication and leadership abilities
• Ability to work collaboratively in a cross-functional team environment

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $180,000 - $240,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MN1

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About the Attentive Team

Have you ever received text message marketing from your favorite brand with an incredible offer? Did you know that effective text message marketing is by far the highest ROI marketing channel? And did you know that customers are increasingly preferring to interact with brands through text? That is what we do at Attentive. We help the world’s largest brands interact with their clients at the right time and with the right message. Our platform powers more than 400 million messages per day, approaching 100 billion per year.

We’re building big things!  Check out our tech blog here: https://tech.attentive.com/

About the Role

Our Business Intelligence team transforms complex data into actionable insights and impactful reporting. We empower clients and internal teams with the metrics, analytics, reports, and visualizations needed to make informed decisions and shape strategies that drive meaningful growth. Joining our team offers a dynamic career opportunity to collaborate with some of the most talented data professionals in a high-performance, high-impact environment.

As a Software Engineer on the BI Tooling & Platform team, you will have the opportunity to shape the foundation on which our metrics are built and retrieved. You will collaborate with talented engineers, product managers, and other internal stakeholders to create innovative applications that empower our BI Team to deliver metrics that our customers trust and rely on.

What You’ll Accomplish

• Collaborate and negotiate with Product Management to meet the user’s needs without sacrificing quality or accruing tech debt. You deeply loathe regressions and take proactive steps to protect against them through a variety of testing techniques.
• You are constantly improving the quality of the project you are working on, both via code contributions as well as long-term advocacy for larger-scale changes.
• Build amazing consumer experiences, taking responsibility for code quality, scalability, reliability and performance.
• Collaborate with subject matter experts, fellow developers, and internal stakeholders to turn business goals into achievable technical roadmaps.

Your Expertise

• 3+ years of professional experience in software development focusing on data engineering and backend systems.
• Advanced proficiency in Java, with a deep understanding of object-oriented programming principles.
• Proficiency in python programming, Experience with Apache Airflow, Snowflake, containerization technologies (e.g., Docker, Kubernetes), and designing scalable data ingestion and processing services is highly desirable.
• Hands-on experience designing and developing microservices and APIs.
• Skilled in working with both relational and non-relational databases, as well as streaming technologies.
• Proven track record of architecting and delivering high-scale, high-quality applications.
• Demonstrated excellence in execution, balancing the urgency of speed with the necessity of quality.
• Excellent communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.
• Comfortable navigating ambiguity and translating business objectives into clear, actionable deliverables.
• Enthusiastic about exploring and adopting new technologies, with a pragmatic approach to selecting tools that align with project goals.

Nice to Haves

• Proven experience working with data, including SQL, data analysis, and data engineering.
• Strong familiarity with AWS services, cloud infrastructure, and workflow orchestration, GraphQL.
• Experience with messaging systems or streaming platforms such as Kafka or Pulsar.
• Practical knowledge of DevOps practices and tools, including Docker and Kubernetes, for containerization and orchestration.
• Familiarity with AI tools (e.g., Claude and Codex) to explore opportunities for up-leveling the team's capabilities and company performance.

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $135,000 - $175,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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About the Role
We’re looking for a highly driven Senior Software Engineer to join our Streaming team, which powers the backbone of Attentive’s messaging and personalization platform. Our event streaming systems handle over 2 million messages per second and sit at the heart of how product and data engineering teams build real-time, customer-facing experiences.

What You’ll Accomplish

• Architect and evolve Attentive’s next-generation event streaming platform: Design high-throughput, low-latency solutions that power mission-critical messaging, personalization, and data integration use cases across Attentive’s ecosystem
• Enhance self-service for product engineering and data teams: Build and refine self-serve tools for event observability, debugging, load testing, and system configuration, empowering teams to experiment and ship quickly
• Simplify and modernize streaming architecture: Remove unnecessary abstraction layers, enable direct access for power users, and ensure the platform is flexible for both “paved path” and advanced use cases
• Solve complex distributed systems challenges: Improve event delivery reliability, cost efficiency, and system integration for real-time and batch workloads
• Champion best practices and technology selection: Stay ahead of industry advancements in event streaming, advocating for tools and approaches that balance innovation with long-term reliability
• Collaborate across engineering: Partner with product, data, and infrastructure teams to launch new customer-facing features, integrations, and scalable solutions built on streaming infrastructure

Your Expertise

• 5+ years experience architecting and supporting high-throughput, distributed systems at scale—especially those involving event streaming or messaging platforms
• Deep understanding of the internals of distributed streaming frameworks such as Kafka, Flink, Pulsar, and/or Spark
• Proficient in Java (Spring Boot) and familiar with modern development practices, including object-oriented design, data structures, and algorithms
• Able to debug issues across the stack—from message serialization and event schemas to network and JVM tuning—and communicate tradeoffs clearly
• Familiar with resource scheduling, data locality, and how infrastructure choices impact cost and system behavior
• Experience with observability and developer tooling for streaming (e.g., tracing, metrics, replay).Infrastructure-as-code expertise (Terraform, Helm), comfortable with Kubernetes (EKS) and cloud-native environments
• Track record of modernizing platforms: sunsetting legacy systems, moving to managed services, or implementing self-service capabilities
• Excited by new technologies, but pragmatic about introducing them—focused on solving real business problems

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $150,000-$210,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-AB2

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About the Role

Our Engineering team creates innovative product experiences that power personalized marketing at massive scale. We develop cutting-edge applications and systems that process 100s of billions of messages and events per year, enabling marketers to connect effectively with hundreds of millions of consumers. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented engineers in a high-performance and high-impact culture.

As a Senior Software Engineer in our Intelligent Messaging, you will pioneer the future of personalized 1:1 marketing by architecting robust, scalable backend systems powered by advanced AI and LLMs, including cutting-edge Generative AI and GPT technologies. Collaborating with top-tier engineers, data scientists, product managers, and designers, you’ll craft the foundation and reshape the platform of multi-channel messaging experimentation to support innovative, AI-driven applications that empower marketers to forge deep, meaningful connections with consumers at scale. Your impactful work will drive the delivery of billions of tailored messages, transforming consumer shopping experiences and fueling success for the world’s leading brands.

What You’ll Accomplish

• Develop and maintain scalable backend systems for our customer-facing products, ensuring high performance and reliability.
• Collaborate with cross-functional teams to build applications that support multi-channel communications for marketers.
• Implement and optimize systems that process and deliver billions of messages daily.
• Improve code quality through code reviews, testing, and advocating for best practices.
• Identify and address technical debt to ensure the long-term health of our codebase.
• Drive architectural design and technical decisions, and stay current with emerging technologies to enhance our products.

Your Expertise

• 5+ years of professional experience in software development focusing on backend systems.
• Proficiency in Java, Python, or Go, with a strong understanding of object-oriented programming.
• Experience building and maintaining scalable, high-performance applications.
• Proven ability to collaborate effectively with cross-functional teams.
• Solid understanding of software development best practices, including code reviews, writing tests, and continuous integration.

Nice to Haves

• Experience with service-oriented architecture and distributed systems.
• Familiarity with AWS services and cloud infrastructure.
• Knowledge of databases such as DynamoDB, Postgres, or Redis.
• Experience with messaging systems or streaming platforms (e.g., Kafka, Pulsar).
• Familiarity with frontend development with React and TypeScript.
• Experience with DevOps practices and tools such as Docker and Kubernetes.

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS.
• Infrastructure tooling includes Istio, Datadog,Terraform, CloudFlare, and Helm.
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS.
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and PlaywrightOur automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas.

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $190,000 - $230,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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About the Role

Our Business Intelligence team transforms complex data into actionable insights and impactful reporting. We empower clients and internal teams with the metrics, analytics, reports, and visualizations needed to make informed decisions and shape strategies that drive meaningful growth. Joining our team offers a dynamic career opportunity to collaborate with some of the most talented data professionals in a high-performance, high-impact environment.

What You’ll Accomplish

• Engage with cross-functional product and engineering teams to define analytics requirements and metrics.
• Build robust, exec-facing dashboards to support key business decisions across the organization.
• Design, build, and maintain scalable dbt and Looker data models that support analytics, reporting, and domain ownership.
• Use data modeling, statistics, and other analytical techniques to extract and analyze data from large datasets, identifying trends, patterns, and anomalies to drive insights.
• Develop and manage our data analytics platform Looker.

Your Expertise

• Bachelor's degree in Computer Science, Mathematics, Statistics, Finance, or related field, or equivalent professional experience.
• At least 4 years of experience in analytics or business intelligence, including proficiency with data visualization tools such as Looker or Tableau.
• Proven expertise in writing, optimizing, and utilizing SQL queries within a business context.
• Familiarity with infrastructure components, ETL processes, and reporting/analytic tools and environments.
• Strong ability to manage and execute fast-paced, dynamic projects with a high degree of organization and independence.
• Ability to perform rigorous data analysis when needed to support high-impact business and product decisions.
• Effective communication skills for presenting analysis results to stakeholders, fostering collaboration, and influencing decision-making across teams.

Nice to Haves

• Experience using dbt, Airflow, or other modern ELT/ETL workflows.
• Experience leveraging AI/LLM tools (e.g., ChatGPT, Claude Code) to accelerate analytics workflows, including SQL generation, data exploration, and documentation
• Experience building dashboards and analyses using tools like Hex, Jupyter, or other reproducible notebook platforms
• Proficiency in Python, R, or similar programming languages for data analysis and statistical modeling
• Experience contributing to or establishing modeling standards, testing frameworks, or CI/CD workflows for analytics code.

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $110,000 - $155,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-DNI

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About the Role

Attentive’s streaming platform is the backbone of our real-time messaging and personalization ecosystem, powering billions of events and processing millions of messages per second. It enables teams across the company to build responsive, data-driven products at massive scale.

We’re looking for an Engineering Manager to lead the Streaming Platform team, responsible for evolving and operating the core infrastructure that powers event ingestion, processing, and delivery across Attentive. In this role, you will combine strong technical leadership with people management to drive the next generation of our streaming architecture balancing reliability, scalability, and developer productivity.

You’ll work at the intersection of infrastructure, data, and product engineering, partnering closely with teams across the organization to ensure our streaming platform unlocks innovation in personalization, experimentation, and growth.

This is a high-impact role for a leader who thrives on scaling distributed systems and building high-performing teams in a fast-moving environment.

What You’ll Accomplish

Technical & Platform Leadership

• Define and drive the technical vision and roadmap for Attentive’s streaming platform (Kafka, Pulsar, Flink, etc.), aligning with company-wide goals.
• Evolve the streaming platform to support AI/agent-driven workloads, including real-time feature pipelines, low-latency inference, event replay, and closed-loop feedback systems for continuous learning and decisioning.
• Partner with ML and data teams to define standards and primitives (data contracts, observability, consistency) that enable reliable integration between streaming systems and AI agents while maintaining scalability, debuggability, and platform simplicity.
• Oversee the design and evolution of high-throughput, low-latency, and cost-efficient streaming systems that power mission-critical use cases.

Team Leadership & Execution

• Build, mentor, and lead a high-performing team of engineers, fostering a culture of ownership, collaboration, and continuous improvement.
• Balance hands-on technical involvement with people leadership, providing guidance on architecture, design, and execution.
• Drive effective planning, prioritization, and delivery across multiple initiatives while maintaining high standards for quality and reliability.

Developer Experience & Platform Adoption

• Champion improvements to the streaming developer experience, including tooling for observability, debugging, testing, and configuration.
• Enable product and data teams to move faster by building self-service capabilities and paved paths, while supporting advanced use cases for power users.
• Promote best practices in event design, schema management, and system usage across the organization.

Cross-Functional Collaboration

• Partner with product, data, infrastructure, and ML teams to deliver scalable, real-time solutions for customer-facing features.
• Act as a bridge between platform and application teams, ensuring alignment on priorities, tradeoffs, and system capabilities.
• Influence broader engineering strategy around real-time systems, data infrastructure, and platform architecture.

Operational Excellence

• Ensure high standards for reliability, observability, and incident response across the streaming ecosystem.
• Drive improvements in system performance, cost efficiency, and scalability.
• Establish and maintain best practices for monitoring, alerting, and debugging distributed systems at scale.

Your Expertise

• 9+ years of experience in software engineering, with 2+ years in engineering management or technical leadership roles.
• Strong background in distributed systems and high-throughput data infrastructure, particularly event streaming or messaging systems.
• Experience with technologies such as Kafka, Pulsar, Flink, Spark, or Kinesis, and a deep understanding of their tradeoffs and operating models.
• Proven ability to lead complex platform or infrastructure initiatives spanning multiple teams.
• Solid backend engineering skills (preferably Java/Spring Boot) with the ability to engage in technical design and code reviews.
• Experience building and operating systems with a focus on scalability, reliability, and debuggability.
• Familiarity with cloud-native infrastructure (AWS, Kubernetes/EKS) and infrastructure-as-code (Terraform, Helm).
• Strong understanding of observability practices (metrics, tracing, logging) in distributed systems.
• Demonstrated ability to hire, mentor, and grow engineers, and foster an inclusive, high-performance culture.
• Excellent communication skills, with the ability to clearly articulate technical tradeoffs and influence stakeholders.

What We Use

• Event Streaming: Apache Kafka, Pulsar, Flink
• Cloud Infrastructure: AWS (EKS/Kubernetes), Terraform, Helm, Istio, CloudFlare
• Backend: Java, Spring Boot, Gradle, DynamoDB, Postgres, Redis
• Observability: Datadog, distributed tracing, custom tooling
• Data & Automation: Python, Airflow, and integrations with ML/analytics systems
• Frontend (for tooling): React, TypeScript, GraphQL

Why This Role

• Own and shape the core real-time platform that powers Attentive’s entire product ecosystem
• Lead a team working on systems at massive scale (billions of events, millions/sec throughput)
• Influence company-wide architecture and unlock new capabilities in personalization and experimentation
• Grow as a leader while staying close to deep technical challenges in distributed systems

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $210,000 - $265,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-DNI

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

About the Role
The Onsite Customer Growth team builds the features that help Attentive’s customers grow directly on their websites. Our mission is to accelerate list growth and improve conversion by delivering creative, high performing onsite experiences powered by strong engineering and intelligent AI driven optimization.

What You’ll Accomplish

• Lead, mentor, and grow a high performing engineering team responsible for building the backend systems powering onsite customer growth products
• Set the technical vision and roadmap for backend services, APIs, and data driven systems that power personalized onsite experiences at scale
• Partner closely with AI, data, and product teams to develop intelligent capabilities that improve performance and user experience
• Ensure the reliability, scalability, and performance of the systems that support customer growth and real time user interactions
• Drive best practices in design discussions, code reviews, architecture decision making, and operational excellence
• Foster a learning oriented team culture that encourages collaboration, curiosity, ownership, and continuous improvement
• Own delivery of key product initiatives, balancing long term platform investments with near term business objectives
• Promote clean, maintainable, well tested code and high engineering standards across the team

Your Expertise

• 7+ years of professional backend software engineering experience, including at least two years managing or leading engineers
• Strong proficiency in one or more modern programming languages such as Java, or Typescript
• Experience designing and operating distributed systems, APIs, and microservice architectures at scale
• Hands on familiarity with cloud platforms such as AWS and containerization technologies such as Docker or Kubernetes
• Deep understanding of databases, messaging systems, or streaming technologies such as PostgreSQL, Redis, or Kafka
• Track record of building reliable, scalable, high throughput systems that support customer facing products
• Demonstrated ability to coach and develop engineers, drive team alignment, and create an inclusive, collaborative engineering environment
• Strong communication and cross functional partnership skills, with the ability to work effectively with AI, data, product, and design teams
• A mindset rooted in ownership, curiosity, and a passion for building meaningful systems that drive measurable customer impact

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $193,000 - $250,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MN1

By applying for this position, your data will be processed as per Attentive's Privacy Policy.

Octus is seeking a Principal Data Engineer to roll up their sleeves and build scalable, production-grade data pipelines and infrastructure. You'll be a hands-on technical leader — writing code daily, solving hard engineering problems, and helping elevate the team around you through doing. Spanning Snowflake, Databricks, and AWS, you'll be deeply involved in the day-to-day development of the data platform that powers Octus's products, data, and automation initiatives. The ideal candidate is an expert in Python and SQL who thrives in an execution-focused environment and has deep experience building modern data pipelines and lakehouse solutions.

Responsibilities

• Build and maintain end-to-end data pipelines — from raw ingestion through transformation and delivery — across diverse data sources (APIs, web data, internal feeds, etc.).
• Hands-on development of scalable, production-grade pipelines within Databricks, including Delta Lake table management, Workflows, and cluster optimization.
• Build and maintain data models, schemas, and transformation logic in Snowflake, optimizing for performance and reliability.
• Develop and manage Databricks environments including Unity Catalog, Delta Live Tables, and integration patterns that support both internal data consumers and external sharing use cases.
• Build and manage orchestration workflows using AWS services (MWAA/Airflow, Lambda, ECS, SQS, MSK) and Databricks-native orchestration where appropriate.
• Implement and maintain infrastructure as code (IaC) using Terraform, ensuring reproducibility and compliance with cloud standards.
• Establish and enforce best practices in data modeling, schema design, and ETL/ELT processes for high-volume structured and semi-structured data across Snowflake and Databricks.
• Ensure data quality, lineage, and observability through automated testing, monitoring, and alerting across all pipeline layers.
• Collaborate closely with technology leadership to align data platform development with business strategy and product goals.
• Stay at the forefront of industry trends in data engineering, lakehouse architecture, and cloud-native data platforms.

Requirements

• Strong foundation in software engineering principles, including SOLID design, modularity, and scalability.
• Expert proficiency in Databricks, including Delta Lake, Unity Catalog, Delta Live Tables, MLflow, and Databricks Workflows.
• Deep experience with Snowflake, including data modeling, performance optimization, and integration with upstream/downstream pipeline tooling.
• Expert proficiency in Python for data pipeline and automation development.
• Advanced SQL skills with experience optimizing complex queries and data models at scale.
• Proven experience designing and maintaining cloud-native data pipelines on AWS (e.g., MWAA/Airflow, Lambda, ECS, SQS, Glue, S3, Redshift, etc.).
• Experience implementing and managing Terraform or similar IaC frameworks.
• Strong understanding of lakehouse architecture patterns, data ingestion, transformation, and orchestration, including familiarity with ML/AI pipeline integration patterns.
• Familiarity with CI/CD pipelines, automated testing, and modern DevOps practices.
• 8+ years of experience in data engineering or backend development, with a focus on scalable data solutions.
• Demonstrated experience leading data infrastructure projects end-to-end and mentoring senior engineers.
• Familiarity with containerization (Docker) and workflow orchestration best practices.
• Excellent communication, collaboration, and problem-solving skills.

Nice to Have

• Experience with streaming data technologies (Kafka, Kinesis, Flink).
• Exposure to ML/AI pipeline patterns (feature stores, experiment tracking, model serving) and MLOps tooling, particularly in a cross-functional team environment.
• Experience integrating data quality and observability tools.
• Experience with Databricks as a data sharing and collaboration platform (Delta Sharing, Marketplace).
• Familiarity with Claude Code or similar AI-powered developer tools for accelerating pipeline development and code workflows.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $175,000 - $220,000

The actual compensation will be at Octus' sole discretion and will be determined by the aforementioned and other relevant factors.

Role

We are looking for a backend-oriented Senior Software Engineer to help us advance our clinical AI by designing and building core systems that handle, process, and analyze clinical data at scale. The ideal candidate for this role has a track record of delivering complex features in incrementally valuable releases and with a high bar for quality. While this role focuses on backend systems, strong candidates are able to deliver across the stack.

**This role is fully remote within the US**

What You’ll Do

• Design, build and launch new backend services, capabilities and improve the overall quality of SmarterDx’s apps
• Collaborate across disciplines to understand our users and iterate on new ideas
• Protect patients’ privacy and security through secure coding practices
• Research and advocate for improved techniques, processes, and designs within the team
• Support SmarterDx’s apps in production

What You Bring

• 5+ years of development experience with a focus on backend and cloud-based solutions
• Expertise in Python 
• Experience working with Postgres or a similar relational database
• Experience building cloud-native distributed systems and working with event-driven architectures
• Experience working with data scientists to plan, build, and iterate on deliverables
• Experience working in a security-conscious environment
• Excellent communication and team collaboration skills
• Bachelor’s or Master’s in Computer Science, Engineering, or a related field, or equivalent experience

Nice To Haves

• Experience at a scale-up, or rapid growth, technology company 
• Experience in the health tech domain, particularly in hospital billing systems
• Experience working with Kubernetes
• Experience working with Airflow and tools that handle ELT pipelines
• Experience with Snowflake and dbt
• Experience with full stack ownership and development (Javascript/React)

Our Stack

Python, React, Kubernetes, Postgres, AWS, Terraform,  ElasticSearch/OpenSearch, Airflow, Snowflake

Compensation

$190K to $230K base salary

#LI-DNI

The People Science & Analytics team at Roblox partners with our People, Places, & Systems organization to apply data science, applied statistics, and  analytics to our internal operations. We deliver insights and solutions that shape Roblox's approach to leadership, people development, and organizational culture. As a Data Scientist in the People Analytics pod, you will join this team to solve complex challenges using qualitative and quantitative data, driving strategic decisions across the company. We are responsible for developing and managing Roblox’s HR data warehouse, analytical tools, and reports which support  data-driven HR initiatives and are used by internal stakeholders throughout the company.

You will:

• Serve as an analytics consultant to key partners in HR, Talent Acquisition, and Finance where you will apply your expertise in data science, applied statistics and analytics engineering to build tooling and identify insights that drive strategic and operational improvement - domains located below.
• Conduct end-to-end analyses on large, complex datasets to diagnose operational challenges, tell a compelling story, and provide actionable recommendations to executive leadership.
• Design, build, and maintain data products and automated workflows that scale our team's analytical offerings and support our partners' long-term needs.
• Uphold a high standard for data integrity and analytical rigor, working through ambiguity to produce clear, defensible insights.

You have:

• A MBA / Master's degree, PhD, or equivalent experience in Data Science Statistics, Economics, Operations Research, Computer Science, Applied Math, Physics, Engineering, or other quantitative fields.
• 4+ years of professional experience with SQL.
• 4+ years of statistical programming in R/Python and/or analytics engineering experience in Python
• 4+ years of professional experience with BI Tools (Tableau, Looker, Hex, etc.)
• Proven ability to execute complex and cross functional projects from ideation through completion.
• Strong interpersonal skills and the ability to work through ambiguity to delivery on projects that have driven organizational change.
• Proven ability to explain technical concepts to non-technical audiences and discuss appropriate tradeoffs.
• Highly self-driven and intellectually curious with a growth mindset focused on maximizing organizational impact.
• A consistent track record to learn quickly and works well both independently as well as in a team setting.

At least two or more of the following:

• 2+ years of experience with enterprise HR/People data systems (e.g., Greenhouse, Workday, Qualtrics) and/or experience working with non-technical operations teams.
• 2+ years of experience in causal inference, experimental design, and statistical modeling. 
• 2+ years of experience with data orchestration and transformation tools (e.g., Airflow, dbt) and deploying data pipelines.

People Analytics Domains at Roblox

• Talent Acquisition
• Employee Performance Programs
• Workforce Planning
• People Data Governance
• Facilities and Office Planning
• HR Operations
• Partnering with Internal Tooling to build people products
• Building our People Datalake

Reddit has a flexible workforce! If you happen to live close to one of our physical office locations, our doors are open so you can come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence

We are looking for a talented and driven individual to be a key part of our Analytics Engineering team within the Data Science organization, focused on the Sales and Marketing domain. We are looking for someone who can work closely with Data Scientists and members of Sales and Marketing cross-functional teams to curate, develop, and deploy the right data and analytic tooling to drive Reddit’s business forward and provide a data and tooling foundation that will last decades. Your work will empower thousands of your colleagues to grow our Sales and Marketing reach.

Successful candidates have a strong track record of understanding and deeply caring about the purpose of data to support business goals, and can act as an effective conduit between Data Producers and Data Consumers. This role sits at the intersection of Data Science and Data Engineering, and the ideal candidate has skills, experience, and passion in both areas. 

Responsibilities:

• Be the Analytics Engineering lead within the Sales and Marketing organization and a key contributor to the success of Data Science data quality, performance, and automation initiatives. 
• Be the data steward for Sales and Marketing: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for business tracking, advertiser outreach and acquisition, marketing campaigns, and other data-driven activities. 
• Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. Work closely with engineering to ensure the quality and reliability of these data pipelines. 
• Create user-friendly tools and applications for internal use across Data Science and cross-functional teams, streamlining data analysis and reporting processes. Drive widespread adoption of these tools and applications with a relentless focus on automation, consistency, and reliability. 
• Lead transformational efforts to build a data-driven culture at Reddit by enabling data self-service. 
• Provide technical guidance, mentorship, coaching and/or training to data scientists and other technical partners.
• Serve as a thought partner for data scientists, engineering managers, and leadership on data foundations, communicating and shaping the data foundations roadmap and strategy for Reddit.

Required Qualifications:

• Advanced degree in a quantitative discipline such as statistics, operations research, computer science, applied mathematics, economics, or physics 
• For M.S. holders: 5+ years of industry experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable, code and systems (Python preferred) in a production environment.
• For Ph.D. holders: 4+ years of industry experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable, code and systems (Python preferred) in a production environment.
• Experience working in Sales and Marketing domains.
• Strong programming proficiency in Python, SQL, Spark, Scala, etc.
• Experience with data modeling, ETL and ELT concepts, and patterns for efficient data governance. Experience with manipulating massive-scale structured and unstructured data.
• Experience with data workflows (such as Airflow), data modeling, front-end or back-end engineering.
• Experience in data visualization and dashboard design, including tools such as Looker, Tableau, R visualization packages, streamlit, D3, and other libraries, etc.
• Deep understanding of technical and functional designs for relational and MPP Databases.
• Proven track record of cross-functional execution and collaboration. Excellent communication skills to collaborate with cross-functional stakeholders at all levels of the company, of differing levels of technical acumen.
• Experience in mentoring junior data scientists and analytics engineers.
• Self-starter, ability to work independently and autonomously, as well as part of a team. 

Nice to have:

• Sales and Marketing domain experience
• Past experience collaborating closely with data scientists, sales, and marketing managers

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-Remote #LI-NH1

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers.

WHY CONTENT SAFETY?

Content safety and moderation are paramount to maintaining a positive, engaging, and trustworthy platform experience for our global community. In this role, you will apply your expertise in data science, statistics, and causal inference to strategically define, measure, and improve the detection and mitigation of harmful user-generated content and violative on-platform behaviors. Your focus will be on asset-based content across the platform - including games, avatars, and emerging in-game behaviors - by establishing reliable ground truth datasets and developing robust prevalence measurement methodologies. You will collaborate closely with Product, Engineering, Legal, Policy, and Compliance teams, acting as the quantitative expert who guides our defensive strategy against evolving safety threats and ensures accountability and scalable solutions. This is a critical opportunity to build innovative detection systems, define what we measure, and prove the impact of our safety efforts.

You Will:

• Establish and monitor robust prevalence measurement methodologies to accurately quantify the overall level of harmful content and behavior on the platform, providing the authoritative source of truth for organizational safety goals.
• Develop and validate comprehensive ground truth datasets for harmful UGC and violative on-platform behaviors, ensuring high quality and alignment with the latest platform policies.
• Deepen our understanding of violations by conducting exploratory analysis on current and emerging threat landscapes, providing data-backed recommendations on where Product and Engineering should strategically invest detection and moderation resources.
• Design, implement, and analyze sophisticated experiments for new moderation and safety enforcement features, communicating results to our primary partners in Product and Engineering to guide development, while also collaborating closely with Policy, Compliance, and Legal teams for full strategic alignment.
• Leverage advanced causal inference methodologies to accurately measure the effectiveness and potential systemic impacts of various safety initiatives on player experience and platform integrity.
• Communicate strategic insights and present recommendations to leadership and all cross-functional partners, translating complex statistical findings on prevalence, ground truth quality, and effectiveness into actionable strategies for Product, Engineering, Policy, Compliance, and Legal.
• Partner with ML and Data Engineering teams to ensure model development, reporting, and detection systems are built on statistically sound ground truth and measurement frameworks.

You Have:

• 10+ years of industry experience in data science, economics, analytics, or machine learning engineering
• 7+ years of experience using scripting languages (Python, R), and big data query/processing languages and tools such as SQL, Hive, Spark, and Airflow
• Knowledge of ML and Deep Learning either via formal training or industry experience
• Ability to apply creative first-principles reasoning to solve ambiguous problems
• Experience developing large-scale safety or moderation systems as well as experience with content platforms, specifically user-generated content
• Advanced Degree and/or PhD in Statistics, Computer Science, Physics, Applied Math, Economics, or other related quantitative fields

The Data Engineering team at Roblox plays a crucial role in enabling the company's success by developing and maintaining highly leveraged Core Data Sets, frameworks, and tooling to support the growing demand for analytics. 

As a Principal Data Engineer, you will work to define the data ontology for all of Roblox, establish best practices and standards for data operations and lifecycle management, design and build analytics tooling and frameworks, and influence event instrumentation. Additionally, this role is highly cross-functional, requiring close collaboration with Data Science, Experimentation, and Machine Learning teams to understand customer requirements and analytics applications, as well as with Data Infrastructure and Storage teams to develop integrated solutions. 

Join us and be a part of a dynamic team driving innovation and growth at Roblox.

You Will:

• Partner with Data Science, Data Platform, Product, and Engineering to collect requirements to define the data ontology for all of Roblox
• Lead and mentor a growing team of Data Engineers to support Roblox's ever-evolving data needs
• Design, build, and maintain efficient and reliable batch and streaming data pipelines to model business entities as core data sets
• Develop scalable frameworks and tooling to automate analytics workflows and streamline users interactions with data products 
• Establish and evangelize best practices for data operations and lifecycle management

You Have:

• 8+ years of professional experience working building scalable ETL pipelines on industry standard ETL orchestration tools (Airflow, Dagster, Luigi, Google Cloud Composer, etc.) with deep expertise in SQL, PySpark, or scala.
• 3+ years leading data engineering development directly with business or data science stakeholders
• Built, scaled, and maintained Multi-Terabyte data sets and have an expansive toolbox for debugging and unblocking large scale analytics challenges (skew mitigation, sampling strategies, accumulation patterns, data sketches, etc.)
• Experience with at least one major cloud's suite of offerings (AWS, GCP, Azure).
• Developed or enhanced ETL orchestrations tools or frameworks
• Worked within standard GitOps workflow (branch and merge, PRs, CI / CD systems)

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency, and acumen of our business decisions and to empower and scale product innovations. We cover a wide area of the data spectrum, including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling, economics, and machine learning. Aligned and partnering with product groups, we use this vast tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure the impact / incrementality on our community of players, developers, and advertisers.

WHY ADVERTISING SCIENCE?

Advertising at Roblox is new, facing critical scale, effectiveness, and implementation challenges, while operating in our civility and user focused experiences. As a new strategic area, work will be innovative and impactful. Scientific rigor will be critical in success as we organize our data model, design principled measurement systems, and architect the future of incrementality measurement and actioning, to enable our communities.

In this role, you will contribute to the new Ads Science team within the broader Economy DSA team, collaborating with engineers and product managers to innovate our advertising systems and operations. Work will include data pipeline design and ownership, modeling for ad delivery and targeting, modeling for user segmentation / experimentation, and experimental design and analysis. We are early in this multi-year journey, and seek a dedicated and passionate scientist to help design this vision and execute the innovation to achieve it.

You Will:

• Design and lead offline model evaluation end-to-end (pipelines, frameworks, analysis).
• Contribute to ads ML feature and model improvements, collaborating with engineering to put these in production.
• Build offline evaluation and simulation models for our ads marketplace.
• Accelerate product development through your understanding of the underlying data and your ability to partner with product and technical leaders to provide insights.
• Lead experimental design and analysis for your ads domain.
• Design science roadmaps and experimentation agendas to determine success of product feature launches.

You Have:

• Domain experience in digital ads systems, including ownership of critical analytic or production pipelines.
• 4+ years of industry or academic experience in data science, economics, analytics, or machine learning engineering.
• Expertise in data transformation and programming, and proficiency in developing data pipelines through use of Spark, Hive, and Airflow.
• Experience with auctions and experimentation in market settings.
• Graduate education in a technical field (preferred: rigorous applied training including a graduate degree in economics, statistics, bioinformatics, cognitive science, physics, or similar).

You Are:

• Candid on relative opportunities for impact, and evidence-seeking to update beliefs.
• Passionate about Roblox’s mission to connect a billion people every day with optimism and civility, including through increasing earnings for our creator community.
• A strong communicator. You understand that analysis must be presented in meaningful ways and lead spirited discussions about the findings. You can explain technical concepts to non-technical audiences and discuss appropriate tradeoffs.
• Effective in a collaborative work environment with a track record of simplifying complex and ambiguous problems.

As an Analytics Data Engineer within the Finance team, you will be a key player in shaping our data ecosystem. You will design, build, and maintain scalable data pipelines that transform raw data into a reliable and trustworthy source of truth for the Finance organization and beyond. 

You will be the primary liaison between the Finance and the Data Engineering teams. You will use your domain knowledge of finance to understand their data requirements, translate them into technical specifications, and then build the necessary data infrastructure. Your work will directly impact financial planning, forecasting, and strategic decision-making across the company.

You Are:

• A Data Expert: You have a deep understanding of data warehousing, ETL/ELT principles, and data modeling best practices. You can design and implement robust and scalable data pipelines.
• A Problem-Solver: You are passionate about using data to solve complex business problems. You can break down ambiguous requirements into clear, actionable data engineering tasks.
• Collaborative: You enjoy working with diverse teams and can effectively communicate complex technical concepts to both technical and non-technical stakeholders.
• Detail-Oriented: You have a high bar for data quality and integrity. You take pride in building accurate and reliable data products and you are comfortable owning full quality from end to end.
• Curious and AI-forward:  You are excited by the potential of LLMs, prompt engineering, and the rapidly changing world of AI tooling. You go beyond just using tools like Claude/Claude Code or Cursor—you've experimented with them and are keen to build and integrate entire systems around them.

You Will:

• Design, develop, and maintain robust data pipelines using Python and Apache Airflow to process large volumes of data from various sources (e.g., internal databases, third-party APIs, and external systems).
• Be the subject matter expert on our Redshift data warehouse, optimizing queries and tables, and ensuring data integrity.
• Build and maintain data models that provide a single source of truth for key business metrics and KPIs. 
• Co-develop and implement data quality checks and monitoring with finance business process owners to ensure the accuracy and reliability of our data.
• Document data pipelines, data models, and business logic to ensure maintainability and transparency. 
• Collaborate with Finance stakeholders to understand their data needs and translate them into scalable data solutions.
• Partner with Finance and Data teams to create the AI Business Context layer for financial applications, converting accounting principles, metric definitions, and business logic into structured, AI-interpretable formats.
• Build tools that provide natural language access to financial data, automated anomaly detection and AI-assisted reporting, enabling Finance stakeholders to independently discover insights.

You Have:

• A Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
• 4+ years of experience in a data-focused role, with a strong emphasis on data engineering, business intelligence, or a similar analytics function.
• Proven experience in designing, building, and maintaining production-level data pipelines.
• Demonstrable experience working directly with finance or business operations teams to deliver data solutions.
• Expertise in SQL and experience with a modern data warehouse, preferably Redshift.
• Strong programming skills in Python.
• An interest in learning core financial modeling concepts to understand data use-cases 

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers.

WHY DISCOVERY EXPERIENCES?

We're seeking senior data scientists with expertise in machine learning to join our Discovery Experience team. As IC leaders (individual contributors with a large span of influence), you'll drive strategic decisions for user growth and product innovation, leveraging all data science toolkits (analytics, experimentation, forecasting, and ML solutions) to improve end-to-end consumer journeys on Roblox. The roles will primarily focus on Discovery Experiences. Discovery surfaces (i.e. home, search, matchmaking, notifications) are critical to fostering engagement and long-term relationships with our platform. The complex network of our two-sided marketplace, combined with the ever-evolving metaverse, presents exciting challenges.

This role will report directly into the Senior Director of Data Science (Consumer) and will be based at our headquarters in San Mateo, CA (hybrid, onsite days Tues-Thurs).

You Will:

• Develop foundational solutions to scale the hypothesis generation process across key user engagement touchpoints.
• Contribute directly to the development of ML solutions that power our discovery canvases alongside our sister engineering teams.
• Partner closely with Product and engineering leaders to inform, drive and accelerate innovations in discovery experiences via Insights, frameworks, causal inference solutions and machine learning prototypes.
• Leverage advanced causal inference methodologies to measure the effectiveness of various initiatives, ranging from Roblox events to social features susceptible to network effects.
• Conduct exploratory analysis to identify and advise XFN partners on opportunities for strategic investments.
• Design and implement experiments for new features and communicate results succinctly to non-technical audiences.

You Have:

• Advanced Degree and/or PhD in Statistics, Computer Science, Physics, Applied Math, Economics, or other related quantitative fields
• 10+ years of industry experience in data science, economics, analytics, or machine learning engineering
• 7+ years of experience using scripting languages (Python, R), and big data query/processing languages and tools such as SQL, Hive, Spark, and Airflow
• Knowledge of ML and Deep Learning either via formal training or industry experience
• Ability to apply creative first-principles reasoning to solve ambiguous problems
• Experience developing large-scale recommendation systems as well as experience with content platforms, specifically user-generated content

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers.

WHY DISCOVERY EXPERIENCES? 

Roblox is not just a platform; it is a complex, two-sided marketplace where millions of creators meet over 70 million daily active users. The Discovery Experiences team is the technical heartbeat of this ecosystem. We own the surfaces—Home, Search, Matchmaking, and Notifications—that determine how users navigate the metaverse.

As a Principal Data Scientist, you will own the ranking initiatives that power these canvases. You aren't just building models; you are building the economic and social frameworks that decide which experiences thrive. You will report directly to the Senior Director of Data Science and serve as a high-visibility IC leader driving the roadmap for our most critical consumer touchpoints.

You Will:

• Algorithmic Vision: Lead the development of ML solutions and ranking frameworks that power our discovery canvases. You will move beyond local optimizations to solve for long-term ecosystem health and user retention.
• Strategic XFN Partnership: Act as the primary scientific advisor to Product and Engineering leaders. You will use data to inform, drive, and accelerate innovations via deep-dive insights and ML prototypes.
• Causal Inference & Experimentation: Leverage advanced causal inference methodologies to measure the effectiveness of platform initiatives (e.g., social features or site-wide events) that are often susceptible to complex network effects.
• Foundational Scaling: Develop frameworks to scale the hypothesis generation process, ensuring that our experimentation velocity matches our massive growth.
• First-Principles Problem Solving: Apply creative, first-principles reasoning to ambiguous problems, such as balancing the visibility of established "top tier" experiences with the discovery of new, niche UGC content.

You Have: 

• Advanced degree (Masters or PhD) in a quantitative field (Statistics, CS, Physics, Applied Math, or Economics).
• 10+ years of experience (or 6+ with a PhD) in Data Science, Economics, or ML Engineering, specifically within large-scale recommendation systems or UGC content platforms.
• Expert in the modern data stack (Python, R, SQL, Hive, Spark, Airflow) and have a deep theoretical and practical understanding of Deep Learning.
• Ability to design sophisticated experiments that account for the nuances of a two-sided marketplace and social network effects.
• Ability to distill high-dimensional problems into succinct, actionable narratives for non-technical executive audiences.

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers.

WHY ALT DETECTION?

Our Alt Detection system at Roblox is a frontier challenge in large-scale identity modeling, managing a massive multi-partite graph that currently includes approximately tens of billions of nodes and hundreds of billions of edges. In this role, you will apply your expertise in data science, statistics, and causal inference to strategically define, measure, and improve our alt detection systems. This is integrated deeply within various applications across the company. Within our Safety group, identity modeling is critical to mitigate alternate accounts used by adversarial actors to bypass our safety enforcements. Beyond safety, your work will be critical to systemic growth, used for core growth reporting and understanding true market penetration, in addition to establishing fair creator incentives. And more opportunities to expand this system across safety and non-safety use cases. This is an opportunity to build state-of-the-art detection systems that fuel our safety efforts while directly catalyzing our company’s most important growth levers. 

You Will: 

• Develop ground truth evaluation strategies by integrating diverse signals, ranging from "gold standard" manual labels to automated weak supervision frameworks.
• Calibrate score thresholds across applications, balancing high-precision enforcement needs with high-recall required for growth reporting
• Partner with MLE to identify and validate new behavioral, network, and biometric signals to expand detection coverage.
• Collaborate with Engineering to design modular systems capable of processing billions of candidate pairs and supporting high-concurrency graph traversals.
• Lead the cross-functional integration of identity models into Discovery, Ads, and Creator Success to eliminate fraud and improve the fidelity of platform metrics.
• Conduct strategic research to decode the incentives behind alt creation and develop sophisticated classification taxonomies to guide mitigation strategies.
• Communicate strategic insights and present recommendations to leadership and all cross-functional partners, translating complex statistical findings on prevalence, ground truth quality, and effectiveness into actionable strategies for Product, Engineering, Policy, Compliance, and Legal.
• Partner with ML and Data Engineering teams to ensure model development, reporting, and detection systems are built on statistically sound ground truth and measurement frameworks.

You Have:

• 8+ years of industry experience in data science, economics, analytics, or machine learning engineering
• 6+ years of experience using scripting languages (Python, R), and big data query/processing languages and tools such as SQL, Hive, Spark, and Airflow
• Knowledge of ML and Deep Learning either via formal training or industry experience
• Ability to apply creative first-principles reasoning to solve ambiguous problems
• Experience developing large-scale safety or moderation systems as well as experience with content platforms, specifically user-generated content
• Advanced Degree and/or PhD in Statistics, Computer Science, Physics, Applied Math, Economics, or other related quantitative fields

About the Role

The Ads Applied Data team builds and scales the foundational data infrastructure that powers Moloco’s advertising platform. As a Senior Software Engineer, you will design, develop, and optimize distributed data systems for real-time and batch processing, ensuring reliable and low-latency delivery of data across the ads ecosystem. You’ll work closely with Product, ML, and Data Science teams to enable feature engineering, identity resolution, and advanced user signal enrichment across online and offline pipelines.

Responsibilities

• Design and build large-scale distributed systems for data ingestion (Petabyte-scale), transformation, and serving.
• Partner with ML and Serving teams to support feature engineering workflows, connecting offline data to serving systems.
• Contribute to the evolution of Feature Infra / Feature Store, ensuring scalability, discoverability, and consistency of feature data.
• Collaborate on Identity Graph construction to unify user and device identifiers for more effective signal enrichment and targeting.
• Improve system observability, resilience, and performance in high-throughput, low-latency environments.
• Mentor engineers and help define best practices for data and backend engineering.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, or equivalent technical field.
• 5+ years of software engineering experience with one or more modern languages (Java, Kotlin, Go, C++, C#, or Python).
• Proven experience designing and building large-scale distributed systems and backend services.
• Hands-on experience with data processing frameworks such as Apache Beam, Dataflow, or Spark, and orchestration tools like Airflow.
• Strong understanding of cloud infrastructure (GCP, AWS, or Azure) and data storage technologies (BigQuery, Bigtable, Redis, GCS, Kafka, Pub/Sub).
• Demonstrated experience delivering impactful projects through collaboration with cross-functional teams (Product, ML, Data Science).

Preferred Qualifications

• Experience with Feature Infra / Feature Store architecture and operations.
• Experience in Identity Graph design and construction to enhance user signal quality.
• Deep familiarity with AdTech or Machine Learning infrastructure domains.
• Experience working with Petabyte-scale data and high-availability systems.

About the Role:

We are looking for a Staff Software Engineer to join our Ads Data Warehouse team, which builds and evolves the core data infrastructure that powers all data-driven products and analytics across the company.

The Data Warehouse team is responsible for foundational systems such as data lineage, data catalog, access control, and compliance frameworks—enabling teams to securely and efficiently leverage data for decision-making, analytics, ML modeling, and Ads optimization.

As a Staff Engineer, you will define the technical vision and strategy for the Ads Data Warehouse, ensuring that our infrastructure scales to meet the growing complexity of our Ads ecosystem. You will lead architectural design, drive cross-team initiatives, and mentor engineers across teams. Your work will establish the foundation for reliable, compliant, and discoverable data across the entire company.

Responsibilities:

• Define and drive the technical roadmap and architecture, aligning the direction with product, analytics, ML, and infrastructure needs.
• Lead the design and evolution of core data systems, including data lineage, metadata management, and data catalog systems.
• Partner with cross-functional leaders to establish data governance, access control, and compliance frameworks that ensure data integrity and regulatory alignment.
• Build and scale high-reliability systems that power both real-time and batch data workflows across Ads and analytics use cases.
• Influence engineering culture by defining best practices for data modeling, observability, and developer experience.
• Drive cross-org initiatives to improve data quality, discoverability, and system adoption.
• Mentor senior engineers and help develop technical leadership across the data and infrastructure organization.
• Act as a trusted technical advisor to product and engineering leadership on strategy and scaling challenges.

Qualifications:

• Bachelor’s degree or higher in Computer Science, Engineering, or a related technical field.
• 8+ years of experience in software engineering, with a strong focus on data infrastructure, platform systems, or distributed architectures.
• Proven experience designing and scaling large-scale data platforms or data-intensive systems.
• Strong proficiency in Golang, Python, or Java.
• Deep understanding of distributed systems, metadata management, and data modeling principles.
• Hands-on experience with cloud data platforms (e.g., GCP, AWS, Azure) and data orchestration frameworks (e.g., Airflow, Beam, Dataflow, Kafka).
• Demonstrated ability to define and lead complex technical initiatives that span multiple teams or domains.
• Excellent communication skills, with the ability to influence and align stakeholders across engineering, product, and compliance.

Preferred Qualifications:

• Experience leading the design and development of data governance systems at scale, such as data catalog, data lineage, and/or data asset management.
• Expertise in data governance, access control, and privacy compliance frameworks (e.g., GDPR, CCPA).
• Deep understanding of metadata-driven architectures, data quality frameworks, and observability systems.
• Proven ability to set long-term technical direction, guide multiple teams through architectural transitions, and drive platform adoption.
• Recognized for technical mentorship, thought leadership, and fostering a culture of excellence in data infrastructure engineering.

Overview

Our backend systems power the clients used by millions of customers every year to buy their groceries online. These systems must also support tight integration with the largest retailers in the US and Canada. Engineering at Instacart provides the opportunity to work on challenging scaling problems while also designing the features that will define our industry. You will learn how to build in an open collaborative environment serving millions of requests daily.

Finance data engineering is part of the Data Infrastructure team, working closely with accounting, billing & revenue teams to support the monthly/quarterly book close, retailer invoicing and internal/external financial reporting. The team plays a critical role in defining how financial data is modeled and standardized for uniform, reliable, timely and accurate reporting. This is a high impact, high visibility role owning critical data integration pipelines and models across all of Instacart's products.

The team is still small and many of our bigger initiatives are at an early stage. We expect you to work closely with stakeholders and shape these systems from design, technical decisions, project management to execution. Your input will be critical for driving the Finance Data Strategy and building the platform that Instacart's financial data infrastructure will be built upon.

About the Job

• You will work closely with finance, accounting, billing, and revenue teams to understand their main pain points and translate them into self-serve, reliable, and scalable data solutions.
• You are expected to mentor other team members and be a champion of engineering excellence across the organization.
• You will be part of a small team with a large amount of ownership and autonomy, managing initiatives directly from design through execution.
• You will have the freedom to suggest and drive organization-wide initiatives that shape the financial data vision and roadmap.
• You will own critical data integration pipelines and models, ensuring uniform, reliable, timely, and accurate financial reporting.

About You

Minimum Qualifications

• 8+ years of working experience in a Data/Software Engineering role, with a focus on building data pipelines (specialized in financial data).
• Strong knowledge of cloud based warehouses like Snowflake, Redshift, BigQuery.
• Strong knowledge of common data infra technologies (Python, Airflow, Spark, Iceberg, Delta Lake) in a production environment.
• Expert in data modeling with experience in modeling complex financial data with scalability and usability in mind.
• Expert with SQL and dbt (Data Build Tool).
• Experience building high quality and complex ETL/ELT pipelines including pipelines for accounting/billing purposes.
• Experience with data immutability, auditability, slowly changing dimensions or similar concepts.
• Adept at fluently communicating with many cross-functional stakeholders to drive requirements and design shared datasets.
• An ability to balance a sense of urgency with shipping high quality and pragmatic solutions.
• Experience working with a large codebase on a cross functional team.

Preferred Qualifications

• Bachelor's degree in Computer Science, computer engineering, electrical engineering or equivalent work experience.
• Experience with Snowflake, dbt (Data Build Tool) and Airflow.
• Experience with SOX controlled data systems.

#LI-Remote

Overview

Our backend systems power the clients used by millions of customers every year to buy their groceries online. These systems must also support tight integration with the largest retailers in the US and Canada. Engineering at Instacart provides the opportunity to work on challenging scaling problems while also designing the features that will define our industry. You will learn how to build in an open collaborative environment serving millions of requests daily.

Finance data engineering is part of the Data Infrastructure team, working closely with accounting, billing & revenue teams to support the monthly/quarterly book close, retailer invoicing and internal/external financial reporting. The team plays a critical role in defining how financial data is modeled and standardized for uniform, reliable, timely and accurate reporting. This is a high impact, high visibility role owning critical data integration pipelines and models across all of Instacart's products.

The team is still small and many of our bigger initiatives are at an early stage. We expect you to work closely with stakeholders and shape these systems from design, technical decisions, project management to execution. Your input will be critical for driving the Finance Data Strategy and building the platform that Instacart's financial data infrastructure will be built upon.

About the Job

• You will work closely with finance, accounting, billing, and revenue teams to understand their main pain points and translate them into self-serve, reliable, and scalable data solutions.
• You are expected to mentor other team members and be a champion of engineering excellence across the organization.
• You will be part of a small team with a large amount of ownership and autonomy, managing initiatives directly from design through execution.
• You will have the freedom to suggest and drive organization-wide initiatives that shape the financial data vision and roadmap.
• You will own critical data integration pipelines and models, ensuring uniform, reliable, timely, and accurate financial reporting.

About You

Minimum Qualifications

• 8+ years of working experience in a Data/Software Engineering role, with a focus on building data pipelines (specialized in financial data).
• Strong knowledge of cloud based warehouses like Snowflake, Redshift, BigQuery.
• Strong knowledge of common data infra technologies (Python, Airflow, Spark, Iceberg, Delta Lake) in a production environment.
• Expert in data modeling with experience in modeling complex financial data with scalability and usability in mind.
• Expert with SQL and dbt (Data Build Tool).
• Experience building high quality and complex ETL/ELT pipelines including pipelines for accounting/billing purposes.
• Experience with data immutability, auditability, slowly changing dimensions or similar concepts.
• Adept at fluently communicating with many cross-functional stakeholders to drive requirements and design shared datasets.
• An ability to balance a sense of urgency with shipping high quality and pragmatic solutions.
• Experience working with a large codebase on a cross functional team.

Preferred Qualifications

• Bachelor's degree in Computer Science, computer engineering, electrical engineering or equivalent work experience.
• Experience with Snowflake, dbt (Data Build Tool) and Airflow.
• Experience with SOX controlled data systems.

#LI-Remote

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.

Position Overview

We are seeking an OSS Test & Automation Engineer to join the team responsible for developing our core network platform – OSS. In this role, you will act as the primary owner of OSS workflow automation development and test engineering. Your primary focus will be to build, test, document and maintain automation processes executed within the OSS platform - covering network operations, service assurance, reporting, and partner integration workflows. At the same time, you will tightly collaborate with internal Service Assurance and Service Delivery teams to gather requirements, transfer knowledge about the developed automation processes, and receive feedback about the required improvements and changes. You are not a pure QA resource since you are an automation developer who also ensures what is built is verifiably correct and operates as expected by the end users. 

Key Responsibilities:

• Design, develop, and maintain automation workflows and orchestration scripts executed within our own OSS platform, covering network operations, fault management, service assurance, reporting, and inventory
• Own and grow the automation backlog - identify manual, error-prone, or repetitive operational processes as candidates for automation, estimate effort, and drive items through to production delivery
• Design, implement, and maintain automated test suites that validate automation workflows under both nominal and fault/edge-case conditions
• Execute test plans, document results, track defects, and drive resolution in collaboration with all involved internal teams
• Produce clear test documentation of test plans, test cases, test reports, and coverage summaries
• Cooperate with internal Service Assurance and Service Delivery teams by fostering knowledge transfer, gathering requirements, and jointly identifying next steps in developing new automated workflows and processes
• Proactively identify automation failures, performance degradations, or reliability issues and drive root-cause analysis and remediation
• Continuously improve automation reliability, coverage, and maintainability based on operational feedback and incident learnings
• Act as first line contact and support line for internal Service Assurance and Service Delivery concerning OSS automated processes and workflows already introduced into production
• Maintain clear, accurate documentation for all automation workflows introduced 

Qualifications 

Education:

Bachelor’s degree in computer science, engineering, telecommunications or a related field — or equivalent professional experience.

Experience & Qualifications:

• A minimum of 3+ years of professional experience in automation engineering, test engineering, or a combined software/QA role, preferably in telecom, network operations, or OSS/BSS systems.
• Proven experience designing and building automation workflows, orchestration scripts, or operational automation pipelines — not just test scripts
• Solid proficiency in Python or any other scripting language and familiarity with modern test frameworks (e.g. pytest, Robot)
• Familiarity with at least one workflow orchestration or BPM tool (e.g. Camunda, Apache Airflow, Ansible, or similar)
• Ability to query and manipulate data in SQL and/or NoSQL databases
• Strong command of test strategy design, test case development, test automation frameworks, and defect lifecycle management
• Familiarity with telecom OSS concepts like FCAPS, TMF eTOM framework or similar operational support system concepts
• Practical exposure to network operations workflows and/or service assurance processes
• Working knowledge of NETCONF/YANG, SNMP, or TMF Open APIs as integration surfaces for automation workflows
• Familiarity with OSS platforms, NMS/EMS systems, or network simulation tools used for test environment setup
• Hands-on experience integrating automation with REST APIs and event-driven messaging systems (e.g. Kafka, RabbitMQ, SQS)
• Experience embedding quality gates and automated tests into CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or equivalent)
• Practical experience with monitoring and logging tooling (Prometheus, Grafana, ELK stack, or equivalent) for making automated workflows observable in production
• Comfortable developing, deploying, and debugging automation in Linux

Soft Skills:

• Strong problem-solving mindset with a bias toward automation and operational efficiency
• Collaborative and communicative — comfortable working in a globally distributed team
• Ownership mentality - take responsibility for end-to-end reliability of systems under your care
• Adaptable and self-directed, with the ability to manage competing priorities in a fast-paced environment
• Meticulous attention to detail in documentation, change management, and operational procedures 

Technology Stack:

• Python (automation, scripting, test frameworks)
• Camunda, Apache Airflow, Ansible, or equivalent BPM/orchestration tooling
• Pytest, Robot Framework, or equivalent
• Postman, requests library, or similar
• GitHub Actions, GitLab CI, Jenkins, ArgoCD
• Prometheus, Grafana, ELK stack, structured logging
• REST, gRPC, Kafka, RabbitMQ, TMF Open APIs, NETCONF/YANG
• Databases:
  • PostgreSQL / MySQL (SQL)
  • MongoDB, Cassandra, or equivalent (NoSQL)
  • InfluxDB or similar (Time-series DBs)
• Docker, Kubernetes (working knowledge for deploying automation workloads)
• Git (GitHub / GitLab)
• Confluence, test case management tools (e.g. TestRail, Xray, or equivalent)

Physical Requirements 

• Ability to work in a standard office or remote home-office environment and use a computer for extended periods
• Ability to participate in occasional after-hours incident response actions

This job description may not be inclusive to the duties and responsibilities listed. Additional tasks may be assigned to the employee from time to time or the scope of the job may change as needed by business demands. 

Position Overview 

We are seeking a Lead Data Engineer to serve as a senior individual contributor—equivalent to a Staff or Principal Data Engineer—with full ownership of analytics data architecture and engineering standards. This hands‑on technical leadership role is part of a high‑impact analytics team responsible for enabling data‑driven decision‑making across satellite network planning, capacity and demand forecasting, network operations, and performance analytics. 

The Lead Data Engineer will design, build, and operate scalable, production‑grade data pipelines and analytical infrastructure to ensure high‑quality; reliable data is consistently available across global planning and operational workflows. This role defines how operational, network, and business data is ingested, modeled, governed, and consumed—transforming complex, heterogeneous datasets into trusted, decision‑ready analytics assets. 

While this position does not include people management, it carries significant technical ownership and influence. The Lead Data Engineer drives architectural strategy, establishes engineering best practices, and mentors analytics professionals to elevate data engineering maturity across the organization. 

 Success in this role is measured by enabling fast, confident, and consistent data‑driven decision‑making—not platform uptime alone. The focus is on delivering durable analytics foundations that support insight, alignment, and execution at scale 

Key Responsibilities 

Data Architecture & Platform Ownership 

• Own the end‑to‑end analytics data architecture, including ingestion, modeling, governance, and consumption patterns. 

• Design, build, and maintain scalable, reliable data pipelines supporting forecasting, network planning, and operational analytics. 

• Establish and operate a lakehouse‑style architecture (raw → normalized → curated). 
• Integrate diverse, complex operational and telemetry data sources into unified analytical and semantic models. 

Analytics Enablement & Decision Systems 

• Translate ambiguous business needs into durable data products, including curated datasets, semantic layers, and standardized KPIs. 

• Define KPI frameworks with consistent definitions, calculations, and refresh logic across teams. 

• Enable self‑service analytics by delivering trusted, well‑documented, discoverable datasets for BI and advanced analytics. 

  Data Quality, Reliability & Governance 

• Implement automated validation, monitoring, and freshness checks across critical pipelines. 

• Identify and resolve systemic data issues proactively, ensuring uninterrupted operational insights. 

• Design schemas and pipelines with governance needs in mind, including lineage, auditability, and certification. 

  Technical Leadership & Standards 

• Serve as the technical authority for analytics engineering and own architectural decisions. 

• Establish and enforce engineering best practices, including testing, version control, documentation, and modular SQL/Python patterns. 

• Mentor analysts and engineers to raise the quality and reliability of data products. 

• Capture metadata and ownership for scalable governance and enterprise cataloging. 

  Qualifications 

Education 

• Bachelor’s degree in computer science, data engineering, information systems, or a related technical field required. 

• Master’s degree preferred but not required. 

  Experience 

• A minimum of 7–10 years of experience in data engineering, analytics engineering, or related fields. 

• Proven experience designing and operating production‑grade data systems at scale. 

  Preferred Qualifications 

• Experience in telecom, satellite networks, IoT, or other high‑volume telemetry data environments. 

• Familiarity with predictive analytics, forecasting workflows, or ML‑driven feature pipelines. 

• Hands‑on experience implementing data quality frameworks, metadata systems, or data lineage tooling. 

• Experience supporting enterprise analytics on a global scale. 

  Soft Skills 

• Strong interpersonal skills and ability to collaborate across cross‑functional teams. 

• Excellent written and verbal communication skills. 

• Strong problem‑solving, debugging, and prioritization abilities. 

• Ability to operate effectively in fast‑moving, ambiguous environments. 

• Meticulous attention to detail, ensuring accuracy across all documentation and data products. 

• Demonstrated ability to translate complex technical concepts for non‑technical stakeholders. 

  Technology Stack 

• SQL (advanced proficiency for analytics‑grade modeling and transformations) 

• Python (data processing, automation, pipeline development) 

• Cloud platforms such as AWS (preferred), Azure, or GCP 

• ETL/ELT tools such as Airflow, Prefect, or Azure Data Factory 

• Modern data ecosystems including Databricks, Snowflake, Redshift, or similar 

• BI and analytics tools such as Power BI, Tableau, or Looker 

• Version control (Git), CI/CD, and modern testing frameworks 

 Physical Requirements 

• Ability to work in a standard office environment and use a computer for extended periods. 
• Occasional virtual or in‑person collaboration across global teams. 

This job description may not be inclusive to the duties and responsibilities listed. Additional tasks may be assigned to the employee from time to time or the scope of the job may change as needed by business demands. 

Analyst, Commercial Insights – Services 

San Mateo, CA (Collab)/Remote 

Role Overview 

PlayStation is looking for an innovative, detail-oriented, highly motivated Analyst to join our PlayStation Services team. Services sits within the Global Sales and Business Operations organization that manages the PlayStation Plus subscription business, a key revenue generator and innovator for Sony Interactive Entertainment. This role sits within the Planning and Insights team responsible for leading analytics operational excellence in commercial performance, planning, and strategy.  

This role is responsible for insightful and actionable analytics support of our subscription services from a commercial planning standpoint. You will play a critical role in creating data reporting tools, developing methodologies for measuring and forecasting impact to subscriptions, and delivering analytical insights on the performance of offers & promotions, pricing and experience optimizations.  The work you do will directly impact decisions made about the offers and experience made available to PlayStation Plus members. Effective verbal and written communication skills are extremely important, as s/he will collaborate with key stakeholders across a global organization.  

What you will be doing 

• Support the Services Insights team with analysis of commercial and engagement trends across the PlayStation Plus user base, using these insights to inform strategic decisions and improve performance measurability 

• Working across our Commercial, Engagement & Experience and CRO teams, you will be responsible for exploring our subscriptions data for novel insights, deconstructing complex datasets to help improve knowledge of our users 

• Creating recursive frameworks for long term monitoring of business initiatives, helping to identify opportunities for growth and reduce reporting cycle time 

• Working with our Engineering and Reporting teams to democratise insights into actionable outputs 

• Support efforts to optimise our business with experimentation and A/B testing 

• Partner closely with stakeholders within GSBO and other supporting teams to understand and deliver business insights using data 

• Collaborate with data teams across SIE to understand and utilise available tools and resources while contributing learnings and business area expertise to the organization  

What we are looking for 

• Bachelors Degree in a quantitative or computational field or equivalent

• 5+ years experience in analytics related roles 

• Proficient at translating ambiguous business requirements into meaningful analytical insights from start to finish  

• Skilled with SQL, Python and spreadsheet applications (Excel, Google sheets). 

• Knowledge of statistical concepts, subscription metrics and A/B testing 

• Keen attention to detail and ability to deliver high quality analytical work 

• Proven experience creating data visualizations and reports to surface actionable insights  

• Excellent communication skills (written and verbal) 

• Ability to work collaboratively with stakeholders across different teams and levels 

• Strong project management, multi-tasking and organizational skills 

• Ability to adapt quickly in a dynamic, changing, fast-paced business environment 

• Ability to work varying hours as well as a flexible approach to working hours to support global business operations 

Preferred Qualifications 

• Strong technical proficiencies with SQL, Python, Airflow 

• Skilled with visualization tools like Domo, Power BI, Tableau 

• Interest in the gaming industry 

• Knowledge of digital gaming landscape, key players, and competitive offerings 

• Prior experience with subscription businesses preferred