About this role

We are looking for an experienced Senior Business Intelligence Analyst to scale a critically important function responsible for building and maintaining systems, processes and services that enable us to understand financial performance and unlock key business insights at Faire. The ideal candidate for this role will ensure key accounting procedures are automated in ways that are accurate, efficient, easy-to-understand, and scalable. This role will sit in the Finance department and collaborate with team members from a breadth of functional groups across Faire, including Accounting, Finance & Strategy, Engineering and Data Infrastructure. This role will have a tremendous impact on the ability for Faire employees to use data effectively in order to report numbers externally and make impactful decisions internally. As an early member of a burgeoning team, you will have the opportunity to write the roadmap for how we improve access to business critical data and unlock automation that amplifies the impact of a variety of functions. 

What you’ll do 

• Scope, design, create, and manage complex ETL flows that aggregate and synthesize key business performance metrics and financial reporting, ensuring efficient, accurate, and scalable data models using best practices 
• Act as a trusted analytical partner to the Accounting and Finance teams providing technical expertise, gathering requirements from product and operational teams, and enabling data-driven decision-making and accountability by ensuring core ledgers accurately reflect business changes 
• Collaborate closely with Engineering, Data Infrastructure, and other stakeholders as a key translator and process improver, gathering requirements and delivering impactful data solutions that ensure alignment and efficiency across the organization 
• Lead initiatives to drive data strategy, roadmap planning, and prioritization, ensuring alignment with business objectives 
• Act as a thought leader to expand the team’s influence and impact throughout the Finance team and the broader organization 
• Drive workflow automation and innovation across Finance, including identifying and implementing Gen-AI–enabled productivity solutions to modernize processes and increase team leverage

Qualifications

• 5+ years of work experience in Business Intelligence, Analytics Engineering, Data Analytics, or comparable function 
• Expert in SQL with focus on data modeling, large-scale data processing, and tool development for analytics or Financial use cases. 
• Experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms 
• Experience with analytics workflow tools (examples: Airflow, Docker, dbt), data warehousing and storage (examples: Snowflake, BigQuery, Redshift, S3), and data visualization tools (examples: Mode, Tableau, Looker) 

Nice to have: 

• Experience with Python, R or other programming languages 
• BA/BS degree, ideally in computer science, math or another quantitative field 
• Familiarity with version control using Git and proficiency in command-line tools for workflow automation and data manipulation

Salary Range

San Francisco and New York: The pay range for this role is $174,500 to $240,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

WHO WE ARE 

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

The Role 

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

What You’ll Do 

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

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

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

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

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

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

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

Qualifications

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

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

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

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

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

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

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

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

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

Preferred Experience

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

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

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

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

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

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

BENEFITS & PERKS

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

SALARY RANGE

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

PEOPLE & CULTURE AT ZETA

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

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

ZETA IN THE NEWS!

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

#LI-YW1

About the Role

The Data engineering team has been created keeping in mind the importance and criticality of data for the overall success of Chime.  The mission of this group is to build scalable data artifacts and insights that enable accurate, governed, data-driven decision-making.. As a core member of the team, you will have the opportunity to build scalable data pipelines and frameworks.  Additionally, you will have the unique opportunity to architect and build workflows that could potentially become de facto standards for the fintech industry.

The base salary offered for this role and level of experience will begin at $164,000.00 and go up to $227,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

• Be a hands-on data engineer, building, scaling and optimizing ETL pipelines
• Design data schemas and scale them data  for 10x data growth 
• Ownership of all aspects of data - data quality, data governance, schema design, data quality and security
• Develop scalable data architecture and standardized data models that enable self-serve data insights using AI.
• Own the ETL workflows and make sure the pipeline meets data quality and availability requirements
• Work closely with partner teams, like Data Science, Analytics and DevOps

To thrive in this role, you have

• 5+ years experience transforming data to governed and lucid datasets
• 5+ years of hands-on experience to build and deploy production-quality data pipelines
• 5+ years of experience working with stakeholders to provide business insights
• 5+ years of experience writing SQL, Spark, AWS Glue, EMR, Airflow, Python 
• 3+ years of hands-on experience using any MPP database system like Snowflake, AWS Redshift or Teradata
• Track record of successful partnerships with Analytics, Data Science and DevOps teams 
• Understanding of key metrics for data pipelines and has built solutions to provide visibility to partner teams
• Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary.

#LI-Onsite #LI-GC1

About the Role

The Revenue Operations team at Gusto is a full-stack team responsible for data, analytics, and operational excellence in pursuit of scaling our revenue growth. The Go-To-Market Analytics team is one functional area, responsible for defining and owning the metrics for scaling our Sales teams. 

Gusto is looking for a Revenue Analytics Engineer to build and maintain foundational data infrastructure that is crucial to growing and scaling our Sales efforts. In this role, you will partner with our GTM analysts to scope and deliver data products for an audience ranging from company and revenue leadership to operational and frontline sales. In doing so, you will own significant portions of our sales data from end-to-end, focusing on the transformation, design, and visualization workflows. In addition, you will establish best practices for systems design and workflows to maximize usefulness of AI at scale. 

This role will report to the Head of Go-To-Market analytics, and partner closely with Data Science, Data Platform, and Business Technology teams. 

Here’s what you’ll do day-to-day:

• Establish relationships with internal stakeholders to determine business needs, scoping and delivering solutions through data products
• Design, build, and maintain data pipelines and dashboards to automate “keep the lights on” work out of manually-managed processes
• Build a data foundation by incorporating business logic into raw data tables, laying the groundwork to enable value-add insights
• Create a dynamic reporting environment based on stakeholder needs
• Identify data discrepancies and set best practices for data logic to create a clean and well-documented environment
• Collaborate with broader data organization as steward to the definition and process management of core Gusto metrics

Here’s what we're looking for:

• Education or work experience in Engineering or Computer Science, or a related technical field 
• 7+ years of experience in an analytics engineering, business intelligence, or technical data analytics role
• Experience with SQL and ETL optimization techniques, especially within cloud-based data warehouses like Redshift, Snowflake, etc.
• Command-line experience and familiarity with version control collaboration tools (git)
• Experience with data pipeline management technologies with dependency checking, such as Airflow, as well as schema design and data modeling tools (dbt)
• Experience with data visualization technologies, e.g., Tableau, Looker, Sigma, Mode, Hex
• Experience with Python and data ingestion tools
• Ability to problem-solve open-ended problems and project manage dependencies and timelines to optimal outcomes
• Ability to demonstrate tools, business intuition, and attention to detail for data validation and QA 

Our cash compensation amount for this role is targeted at $138,000-156,000 in Denver & most remote locations, and $168,000-189,000 in New York & San Francisco Bay Area. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

About the Role:

We are looking for a Senior Software Engineer to architect, build, and maintain the data infrastructure at Gusto.  As part of the Data Platform team, you will collaborate closely with Data Science, Business Intelligence, and analysts across Gusto teams to help them achieve their goals. 

The Data Platform position is a software development role with knowledge of data architectures and data delivery. The ideal candidate is passionate about developing software, working with data, and

Here’s what you’ll do day-to-day:

• Architect, build, and refine our infrastructure and tools that enable other teams to work with data.
• Efficiently handle vast amounts of clickstream, database, and third party application data, processing in batch and real-time
• Take full ownership of the solutions you build, working with stakeholders to develop requirements, implement solutions, monitor production, and troubleshoot problems that arise.
• Work as part of a team. We value team players who share their knowledge and like collaborating with others.

Here’s what we're looking for:

• • At least 7 years of software engineering experience.
  • Experience building solutions in the cloud, AWS preferred (Redshift, MSK, EMR).
  • Experience with OLAP databases (Clickhouse)
  • Experience building data pipelines at scale, Airflow and Python preferred.
  • Experience with streaming systems desired (Kafka, Kinesis, or similar).
  • Ability to turn vague requirements into clear deliverables with minimal guidance.
  • Experience building and maintaining a modern data stack in production.

Our cash compensation amount for this role is targeted at $163,000-$204,000/year in Denver, $178,000-$223,000/year in Los Angeles, and $197,000-$247,000/year for San Francisco, New York, and Seattle. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

The Data Engineering team builds tools and systems that make Gusto's data consistent, user-friendly, and helpful. This helps our teams make decisions using data and provide intelligent, customized experiences to our customers.

We're looking for a Senior Data Engineer who can take loosely defined problems and drive them end-to-end—from framing the problem and aligning stakeholders to designing, building, and delivering durable data solutions. You’ll partner closely with analytics, product, and engineering teams to deliver data solutions that drive real business and customer impact.

Preferred Qualifications

• 8-10+ years of industry experience in data engineering building scalable data pipelines and data products
• Strong proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java)
• Proven experience building and maintaining robust data pipelines and ETL workflows, with hands-on dbt experience for reliable, testable, and maintainable data transformations.
• Hands-on experience ingesting data from diverse sources, including APIs, databases, SaaS applications, and event streams.
• Strong foundation in data modeling, schema design, and data quality best practices, with functional experience working on cloud platforms like Snowflake, Redshift, BigQuery, or Databricks.
• Experience implementing CI/CD pipelines, automated testing, and data observability to ensure reliability and trust in data systems
• Familiarity with monitoring, alerting, and incident response for production-grade data pipelines
• Proven ability to optimize performance and cost across data workflows and storage systems
• Functional understanding of how to leverage AI and automation in data engineering — building self-service tools, intelligent pipelines, and agents that automate repetitive tasks
• Exemplar problem-solving skills and ability to work collaboratively in cross-functional teams.
• Strong communication and collaboration skills, with a focus on clarity, empathy, and shared ownership

Compensation Details

Our cash compensation amount for this role is targeted at $155,000-$185,000/yr in Denver, $170,000-$200,000/yr in Los Angeles, and $190,000-$220,000/yr for San Francisco, Seattle, and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.

This role is based in our New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve:

• Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
• Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
• Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
• Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
• Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
• Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
• Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.

About you:

• Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
• 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
• 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
• Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
• Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
• Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

What we’ll offer:

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences 

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid #LI-AA1

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.

This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve:

• Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
• Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
• Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
• Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
• Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
• Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
• Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.

About you:

• Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
• 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
• 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
• Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
• Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
• Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

What we’ll offer:

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences 

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid #LI-AA1

We are looking for a Staff Security Software Engineer who is passionate about detecting and mitigating abuse in the Cloud. 

As a Staff Security Software Engineer at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. This role reports to the Senior Manager of Security Engineering within the Security organization. You should have experience developing and maintaining software systems in a complex, high-scale environment, analyzing outcomes and communicating insights to stakeholders, and rapidly devising solutions that are in alignment with overall business goals. Our team is focused on enabling DigitalOcean to scale safely by building systems that detect and prevent abuse on our platform. We highly value collaboration and growth, and work closely with other teams in the Security organization to deliver high quality solutions and also build tooling to boost their efficiency.

Our customers trust us with their data and operations, and we take that responsibility seriously. Security at DO means solving highly complex problems on a large scale that have real impact for our customers, our products, and for the larger internet community.

What You’ll Do:

• Design, develop, and deploy resilient services and tooling that provide security capabilities at scale, primarily in Go, with some work in Javascript and Python.
• Research and design automated approaches to detecting and actioning abuse and misuse of DigitalOcean products and services.
• Work with product and engineering teams to design and implement secure architectures.
• Design and build internal tools that enable our Security Operations Center to do more, faster.
• Measure the efficacy of our services and tools, using logs, metrics, and audit records, to drive reporting and decision-making, leading to iterative and transformative security improvements as DigitalOcean scales. All while being mindful that security should be an efficiency enabler for the business, not an obstacle.

What You’ll Add to DigitalOcean:

• 8+ years of hands-on experience in software engineering projects, ideally with a security focus, in a complex, high-scale SaaS or IaaS environment. You are an expert in writing robust code with good test coverage and demonstrated success in delivering projects.
• Understanding of cloud-native services and infrastructure provisioning (e.g. compute, storage, networking).
• Deep familiarity with cloud services & infrastructure—compute, storage, network, managed services—and related abuse tactics, including DDoS, spamming, phishing, cryptomining, and bot networks.
• Strong analytical and reporting skills, with proficiency in SQL and data warehouse querying (e.g., Snowflake, Redshift, BigQuery)
• A customer-first mindset—you aim to maximize abuse prevention while avoiding false-positives that could impact high-value customers.
• Excellent communication and documentation skills; you can clearly articulate patterns, mitigation strategies, and tradeoffs to both technical and non-technical stakeholders. You have a record of partnering with internal engineering teams and non-technical stakeholders to gather requirements and tackle security problems across an entire stack with empathy and creativity.
• High integrity, strong judgment, and a track record of working independently on high-impact investigations and policy decisions.

Bonus qualifications:

• Experience with microservice architectures, asynchronous and event-driven processing, and synchronous gRPC/HTTP-based requests.
• Experience in building secure by default services and applications.
• Familiarity with technologies such as gRPC, Docker, Elasticsearch, Prometheus/VictoriaMetrics, Kubernetes, and GitHub Actions.
• Experience with Looker, Snowflake, dbt, and Airflow

Compensation Range: 

• $199,680 - $249,600

*This is a remote role

#LI-Remote

SoFi is seeking an experienced and motivated Senior Staff Data Engineer to be the technical leader of our Data Engineering group within the SoFi Data Platform(SDP) division. The mission of the SDP division is to activate data throughout SoFi, enabling the creation of personalized and delightful experiences for our members. 

The Role:

In this role, you will have the opportunity to directly impact, influence and lead the direction and architecture of our next gen AI powered SoFi Data Platform(SDP), and elevate data reliability through AI enabled workflows, tooling and practices. You will get the chance to lead, define, and take on complex and interesting problems as part of a fast-paced, highly collaborative organization. The ideal candidate will be a mentor, technical leader and a team player who is hands-on and comfortable driving solutions from initial architecture to implementation and adoption with a strong sense of ownership and drive for delivery. 

What You’ll Do: 

• Technical Leadership & Strategy: As a technical leader, you will be at the heart of SoFi’s data platform providing primary technical authority and strategic guidance to the data engineering group. 
• Architectural Excellence: Lead the architecture and delivery of large-scale, high-performance data pipelines and processing frameworks. Design scalable data models that support analytics, AI/ML and real-time data needs.
• Platform Innovation: Drive the adoption of cloud-native technologies, automation frameworks and reusable components that improve development velocity and system reliability across SDP.
• System Optimization: Drive org-wide initiatives to improve data reliability, cost-efficiency, and latency. Design solutions that scale horizontally and vertically to handle ever-growing datasets.
• Cross-Functional Collaboration: Partner with business stakeholders, product and engineering leads to align the data roadmap with SoFi’s business objectives. 
• Governance & Security: Lead the implementation of sophisticated data privacy, security, and compliance frameworks. Enforce data governance policies and practices to maintain data integrity in a highly regulated environment.
• Mentorship: Provide deep technical coaching and mentorship to Staff and Senior data engineers, fostering a culture of continuous learning, rigorous testing, and engineering excellence.
• Workforce Development: Contribute to hiring and training efforts to build a skilled and motivated data engineering workforce. Lead the interview process for senior-level talent and design onboarding programs that accelerate engineering productivity.
• On-Call Support: Be part of an on-call support rotation to support the critical production systems.

What You'll Need: 

• Education: A bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
• Experience: Over 12 years of experience in data engineering and analytics, with at least 4 years in a staff-level or higher capacity. A proven track record of successfully leading enterprise-wide data modernization efforts.
• Tech Stack Mastery: Mastery of the modern data stack: Snowflake / Python / SQL / GitLab / AWS / Airflow/ AI tools like Claude code/Cursor. Understanding and implementation experience of AI agents is a plus.
• Cloud Architecture: Expert-level proficiency in relational and cloud database platforms (Snowflake, Redshift, or GCP) and distributed processing frameworks (Hadoop, Spark, or Kafka).
• Strategic Thinking: Thorough knowledge and passion for data modeling (Kimball/Data Vault), database design, and data architecture principles. Ability to simplify complex, ambiguous issues into actionable technical plans.
• Communication: Exceptional ability to communicate complex technical concepts and trade-offs to non-technical stakeholders and senior management.

Domain Knowledge: Deep experience in a highly regulated and governed sector; experience in the Fintech industry is highly advantageous.

Mercury is redefining *banking for ambitious companies and behind every great financial platform is a data system that people can actually trust.

As Mercury scales, our revenue systems generate an enormous amount of information: signals from remote and in-person meetings, automation tools, product usage, lifecycle events, and analytics pipelines. Turning that activity into clear, reliable intelligence — without brittle pipelines or constant rework — is critical to how we grow.

We’re looking for a Data Strategy & Operations leader to own the data foundations that power revenue execution. This role ensures that revenue data is reliable, interpretable, scalable, and usable as the business evolves and that teams can act on what they see with confidence.

In this role, you will report to the Head of Platforms & Infrastructure and play a central role in shaping how Mercury models, governs, and operationalizes GTM data. You’ll partner closely with Data Engineering, Data Science, Solution Architecture, Platform Engineering. etc.

*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.

Here are some things you’ll do on the job:

• Own the definition, structure, and reliability of data originating from revenue platforms (e.g., Salesforce, GTM tools, automation systems)
• Serve as the primary decision owner for GTM-sourced tables and views used for revenue execution, forecasting inputs, lifecycle tracking, and signal-based workflows
• Design and evolve core GTM data models across Salesforce, ETL, and analytics layers
• Partner with Data Engineering to align GTM schemas with enterprise data models and define clear data contracts between source systems and downstream consumers
• Partner with Data Science / Analytics to ensure revenue data is interpretable, statistically sound, and reflects how the business actually operates
• Own clarity around data ownership boundaries, shared dependencies, and escalation paths when upstream or downstream changes impact revenue integrity
• Define and uphold data quality, freshness, consistency, and documentation standards for revenue platforms
• Monitor and improve pipeline reliability, performance, and scalability, proactively identifying fragile or redundant transformations
• Identify opportunities to automate manual or error-prone data workflows and reduce operational overhead
• Act as a data thought partner to Platforms & Infrastructure, Revenue Operations, Analytics, and Security — advising on feasibility, tradeoffs, and sequencing for data-heavy initiatives

You Should:

• Have 7+ years of experience in data engineering or data systems roles within SaaS or technology companies
• Have deep experience designing and operating production data pipelines
• Be highly proficient in SQL and experienced in data modeling
• Have hands-on experience with modern data stacks (e.g., Snowflake, BigQuery, Redshift)
• Have experience with ETL / ELT tooling (e.g., dbt, Airflow, Census, or similar)
• Understand Salesforce data models and common GTM system architectures
• Be able to translate business concepts into durable, well-structured data models
• Communicate clearly with both technical and non-technical partners

Preferred:

• Experience supporting revenue, sales, or customer lifecycle data
• Familiarity with event-based data platforms (e.g., Data Cloud or equivalents)
• Experience working alongside platform engineering and security teams
• Exposure to data governance, access controls, and compliance considerations
• Experience mentoring or guiding other data practitioners

Compensation:

The total rewards package at Mercury includes base salary, equity, and benefits.

Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

• US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $158,400 - $198,000
• US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $142,600 - $178,200
• Canadian employees (any location): $149,700 - 187,100 CAD

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024.

[Please see the independent bias audit report covering our use of Covey for more information.] 

#LI-SN1

We are looking for a technically skilled, self-motivated, customer-focused manager to lead a team of high energy Support Engineers. In this role you will be responsible for hiring, developing and mentoring team members as well as delivering against key performance metrics. You'll lead process improvements for customer and partner growth, retention, and excellence, while fostering individual contributions and driving cross-functional projects that spark innovation and collaboration. You need to be comfortable working in a fast paced environment and continuously challenge the team to step outside their comfort zone.

Minimum Education Requirement

This position requires a U.S. Bachelor's degree (or foreign equivalent) in Computer Science, Software Engineering, Information Systems, Data Science, or a closely related technical field. This requirement is a minimum and cannot be substituted by work experience alone.

What You Will Be Doing

• Become a product expert. We are a data driven group and expect you to become fully proficient in Sigma.
• Lead a team of exceptional product experts providing the Sigma user base with an excellent customer experience.
• Hire, develop and train a strong team of Support Engineers on an ongoing basis.
• Collaborate with cross-functional groups — Engineering, Design, Product, Customer Success, Sales, and Marketing ensuring delivery of a great customer experience.
• Manage and develop a strategy toward key metrics: CSAT, Initial Response (IR), SLA, Time to Resolution (TTR).
• Continuously refine processes to optimize efficiency, elevating customer support operations.
• Uncover golden insights within Support data, translating them into actionable strategies for continuous improvement.
• Develop a reputation for excellence, high credibility and integrity with peers across the org.

Qualifications We Are Looking For

• 5+ years of industry experience supporting data platforms in an enterprise environment and 2+ years in a people management role.
• Computer Science fundamentals. Strong domain expertise in databases and business intelligence.
• Comfortable with CDW environment/concepts.
• Proficient in SQL and data modeling concepts.
• A proven track record of building trust with customers and bringing issues to resolution quickly.
• Are curious, love to learn and to dig into new technologies and can pick them up quickly.
• Excellent verbal and written communication skills.

Highly Desirable Skills & Experience

• Managed a team supporting a SaaS product.
• Experience working with Snowflake, Redshift, or BigQuery.
• Knowledge of GCP or AWS.
• Startup experience.

Additional Job details

The base salary range for this position is $160k - $185k annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for bonus and stock options, as well as a comprehensive benefits package.

Sigma is growing rapidly, and our Technical Support Engineering team is scaling alongside it to meet the needs of an expanding global user base. As a Technical Support Engineer at Sigma, you will be part of an award-winning team recognized with the 2024 Stevie Gold Award for Customer Service, helping customers solve technical, business, and data challenges using the Sigma platform. You'll work closely with Product, Engineering, and Go-to-Market teams to diagnose complex issues, drive solutions, and contribute to the continuous improvement of our product and support operations.

Minimum Education Requirement

This position requires a U.S. Bachelor's degree (or foreign equivalent) in Computer Science, Software Engineering, Information Systems, Data Science, or a closely related technical field. This requirement is a minimum and cannot be substituted by work experience alone.

What You Will Be Doing

• You will work with Sigma's customers and the pre-sales team to assist with the diagnosis and resolution of complex technical issues.
• Working closely with the development team, you will develop best practices and tools for diagnosing issues and optimizing the service for performance.
• Collaborate with cross-functional groups — backend, frontend, DevOps, design, product, and the go-to-market teams to create a first-class experience for users of our product.
• Participate in quarterly projects and perform periodic on-call duties to improve automation and processes.

Qualifications We Are Looking For

• 2+ years of experience in a customer-facing technical role (Technical Support, Solutions Engineering, or Software Engineering) at a cloud or SaaS provider.
• SQL proficiency — strong grasp of JOINs, Partitions, Window Functions, Aggregations, CTEs, and sub-queries.
• SQL query performance troubleshooting and query plan analysis.
• Proficient in data modeling concepts.
• Ability to chart data into logical visualizations.
• A proven track record of building trust with customers and bringing issues to resolution quickly.
• Excellent verbal and written communication skills.
• A strong desire to build scalable processes for issue resolution — documenting common patterns and building tooling for diagnosing issues.
• Strong collaboration skills and the ability to work with multiple departments to coordinate issue triaging, diagnosis, and resolution.

Highly Desirable Skills & Experience

• Supporting a cloud service in production.
• Experience working with Snowflake, Redshift, or BigQuery.
• Knowledge of GCP or AWS.
• Startup experience.

Additional Job details

The base salary range for this position is $90k - $125k annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for an annual bonus, stock options, as well as a comprehensive benefits package.

If you do not feel that you satisfy all the listed requirements, we encourage you to still apply. We are enthusiastically looking for people that will help us grow our company and sometimes we are imperfect communicators and can’t articulate perfectly what experience is required for a role. We are looking for people that are excited to grow and constantly ask how we can do things better. If you are excited about the opportunity, we encourage you to apply even if you don’t satisfy 100% of the job requirements.

The Analytics Engineer will report to the Senior Manager, Data Platforms & Analytics Engineering. 

As the Analytics Engineer II, you will:

• Build and improve data models that enable faster, more reliable decision-making across Product, Risk, and Analytics
• Reduce bottlenecks by delivering clean, scalable datasets analysts can trust and use independently
• Support both roadmap initiatives and ad hoc needs to keep business teams moving without delays
• Improve data quality and structure so new products and features can be analyzed and launched with confidence

About You: 

• 3+ years in analytics engineering, data engineering, or similar
• Strong SQL and experience building data models that support business use cases
• Experience with dbt and modern data warehouses (Snowflake, Redshift, etc.)
• Comfortable working cross-functionally and translating messy data into usable insights
• Curious, proactive, and motivated to solve problems—not just complete tasks

Even Better:

• Experience with Airflow or similar orchestration toolsBI tools (Looker, Tableau, etc.)
• Exposure to fintech, product analytics, or high-growth environments

Where:

• This role will be based in the US.

Compensation: 

A little about our pay philosophy: We take pride in compensating our employees fairly and equitably. We are showcasing a range of your potential base salary based on the role's location. The successful candidate’s starting pay will also be determined based on job-related qualifications, internal compensation, candidate location and budget. This range may be modified in the future.

Salary Range: $112,500 - $150,000 USD. Employees are also eligible for an annual performance-based bonus and equity.

#LI-GA

The Core Services team within Snorkel AI's Infrastructure organization will own the data platform that powers everything at Snorkel — the pipelines, access layers, event systems, governance, and compute infrastructure that every product team and customer deployment depends on. We are a small team with a large surface area, and we are in the middle of a foundational architecture shift: moving from a single-database data path to a multi-source, event-driven platform with dedicated stores for different workloads (transactional data in Postgres/RDS, analytical data in Snowflake, bulk storage in S3, metrics platform). The decisions being made now will define how data flows at Snorkel for years. You will be making them.

You’ll also shape our AI-native development workflow, contribute in modernizing CI/CD workflow (Buildkite, GitHub Actions), and integrate AI SRE tooling. Your work will directly accelerate developer velocity, reliability, and product quality across the company

What You'll Do

• Build and maintain the shared data access library and SDKs that Platform, Packaging, and Dataset API teams use to read from and write to multiple data sources (Snowflake, S3, RDS). Design interfaces that abstract source-level complexity while providing built-in auth, RBAC enforcement, pagination, and query governance.
• Design and implement event-driven data flows using event brokers,  CDC connectors, schema registry, event routing, dead letter queues. Make sure events flow reliably and failures are visible and recoverable.
• Build the systems that track how data moves through the platform (lineage), enforce who can access what (governance and RBAC), and log what happened (auditing). This includes PII handling, retention policy enforcement, and audit infrastructure for enterprise and federal compliance.
• Instrument the data platform with OpenTelemetry, define and monitor SLOs for query latency and pipeline success rates, and build alerting that catches issues before they become incidents. You will be on-call for the systems you build.
• Contribute to infrastructure cost visibility and optimization -  query cost estimation, workload right-sizing, and routing data to the most cost-effective storage tier for its access pattern.

What You'll Bring

• 8+ years building platform infrastructure, data infrastructure, data platforms, or backend systems with significant data components. You have built and operated pipelines, data access layers, or ETL/ELT systems in production.
• Strong proficiency in Python. Our stack is Python-heavy across Prefect, FastAPI, dbt, and the SDK layer.
• Hands-on experience with SQL and at least two of: Snowflake, Redshift, Postgres. You understand the performance characteristics of each and can write queries that don't bring down production.
• Experience with AWS — S3, RDS, EKS, EventBridge, IAM. Comfortable working in a Terraform-managed environment
• Experience with Kubernetes. Our workloads run on EKS and you will deploy, debug, and scale services on K8s.
• Familiarity with data orchestration tools (Prefect, Airflow, or Dagster) and transformation frameworks (dbt).
• Understanding of data governance concepts — RBAC, PII handling, audit logging, data lineage.
• Fluency with AI-assisted development tools (Claude Code, Cursor, or similar). This is a hard requirement — the team uses these tools daily and we expect engineers to leverage them for code generation, debugging, and investigation.

Nice to Have

• Experience building shared libraries or SDKs consumed by multiple teams — versioning, backwards compatibility, migration support.
• Experience with event-driven architectures — CDC, event buses, schema registries, at-least-once delivery semantics.
• Experience with OpenTelemetry, ClickHouse, or similar observability infrastructure.
• Prior work in regulated environments (SOC 2, FedRAMP, HIPAA) where compliance requirements shaped system design.
• Experience with Ray for distributed compute workloads.

We're looking for a Customer Success Manager with a deep understanding of analytics and business intelligence to join our team. This role is critical for ensuring our customers maximize the value they derive from our platform, with a direct focus on improving Net Dollar Retention (NDR) through strategic account management and growth initiatives.

This is an in-office role based out of the San Francisco office.

Key Responsibilities:

• Strategic Account Management: Build and maintain strong relationships with decision-makers and influencers within our customer base, with a focus on high-value accounts.
• Analytics Expertise: Leverage your deep understanding of analytics and business intelligence to guide customers in optimizing their use of Sigma Computing's platform. Help them understand their data and gain actionable insights.
• NDR Growth: Develop and implement strategies aimed at maximizing NDR. This includes identifying opportunities for upselling and cross-selling, as well as reducing churn through proactive engagement and solution-oriented support.
• Customer Advocacy: Serve as the bridge between our customers and our product team. Advocate for features, enhancements, and integrations that will drive customer satisfaction and retention.
• Success Plans: Collaborate with customers to develop and execute success plans that align Sigma Computing's capabilities with the customer's business goals and objectives.
• Educational Initiatives: Design and deliver training sessions, webinars, and workshops to increase product knowledge, adoption, and engagement among our user base.

Required Skills / Experience:

• Bachelor’s or Master’s degree in Business, Analytics, Computer Science, or a related field.
• 4+ years of experience in a customer success, account management, or consultative role within the SaaS, analytics, or business intelligence industry.
• Strong analytical skills with a proven ability to solve complex problems using data.
• Excellent communication and interpersonal skills, with a knack for building trust and driving engagement.
• Demonstrated ability to manage and grow customer accounts, specifically focusing on net dollar retention.
• Experience with SQL, data visualization tools, and cloud-based analytics platforms highly preferred (Snowflake, Databricks, Redshift, BigQuery)
• ETL experience
• Experience implementing production business intelligence solutions
• Startup experience

Additional Job details

The base salary range for this position is $100k - $125k annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for a variable pay (based on goal achievement), stock options, as well as a comprehensive benefits package.

ABOUT ROCKET MONEY 🔮

Rocket Money’s mission is to meaningfully improve the financial prosperity of millions of people. Rocket Money offers members a unique understanding of their finances and a suite of valuable services that save them time and money – ultimately giving them a leg up on their financial journey.

ABOUT THE TEAM 🤝

Data Platform Engineers at Rocket Money further our mission by building and maintaining the infrastructure that enables our company to understand our users and products through reliable, scalable data systems. We build the foundational platform that ingests, processes, and serves data—enabling our Data Analytics, Machine Learning, and Software Engineering teams to build data products efficiently. We work closely with engineering teams to ensure data is captured correctly at the source, design resilient pipelines, and create self-service capabilities that empower stakeholders.

The Data Platform team is in an exciting phase of growth and formalization. While we have established tools and processes in place (dbt, BigQuery, Terraform), we're actively building the comprehensive standards, practices, and systems that will scale with Rocket Money as it grows. We're looking for engineers who can take ownership and evolve workflows into reliable, well-documented, production-grade systems. This is an opportunity to shape architectural decisions, establish team practices, and define how Rocket Money works with data for years to come.

We have a strong preference for process-oriented systems thinkers who excel in balancing stakeholder requirements, technical debt, and organizational complexity—and who thrive in environments where they need to create structure from ambiguity. You'll need to be comfortable making principled decisions, taking ownership not just of code but of outcomes, and operating with significant autonomy as we build the platform together.

ABOUT THE ROLE 🤹

In this role, you will:

• Be an end-to-end owner of our data platform infrastructure, ensuring its security, usability, and performance. Work closely with analytics engineers, machine learning engineers, and software engineers to ensure the platform meets their needs.
• Make collaborative decisions about data tooling, pipeline design, and governance, and implement opinionated interfaces that facilitate easy and best-practice-aligned development for other teammates.
• Continuously improve failure rates for data sources by moving alerting “to the left”; i.e. catching and quarantining bugs/failures as close to the source as possible.
• Analyze patterns in how source data is generated, modeled, and consumed. Work with stakeholders to implement the best solution when new data sources are added.
• Take ownership of existing tools and workflows that may be functional but lack formal structure, documentation, or reliability measures. You'll assess what's working, identify gaps, and systematically improve systems to production-grade quality.
• Document everything you build knowing that you're creating the foundation others will build upon. Your runbooks, architecture decision records, and system documentation will become the institutional knowledge of our data platform.
• Proactively communicate with multiple stakeholders on platform capabilities, technical constraints, architectural decisions, project priorities, and platform support.
• Confidently juggle multiple projects and priorities in our fast-paced environment and work with stakeholders and platform teammates to ensure infrastructure changes, migrations, and improvements are delivered on schedule.
• Automate aggressively and deliberately; anything from GitHub Actions to Slack Workflows to minimize repetitive tasks. Effectively judge when the level of effort is appropriate and avoid over-engineering.

ABOUT YOU 🦄

• You have 6+ years of experience working with data infrastructure, data engineering, or platform engineering within a fast-paced environment. You are highly proficient with SQL, Python, and cloud-based Infrastructure-as-Code (e.g. Terraform), and comfortable working with bash/shell scripting.
• You have 4+ years of production experience with modern data stacks including data warehouses (BigQuery, Snowflake, or Redshift), orchestration tools, managed ingestion services, and infrastructure as code (Terraform, Pulumi, or CloudFormation).
• You have 2+ years of experience building and maintaining production data pipelines, whether through ELT tools, custom applications, streaming systems, or event-driven architectures.
• You've successfully "professionalized" data infrastructure before—taking scrappy, working systems and evolving them into reliable, well-documented, production-grade platforms. You can articulate what "production-ready" means in a data context.
• You have a bias toward action and aren't paralyzed by imperfect solutions. You understand when "good enough for now with a plan to improve" beats "perfect but six months late." You ship incrementally and iterate based on feedback.
• You're comfortable being the first person to tackle a problem. You don't need extensive mentorship or detailed tickets—you can take a high-level business need and figure out the technical approach. That said, you know when to ask for help and can articulate what you need.
• You take ownership seriously—not just of writing code, but of outcomes. When you build something, you implement monitoring, write runbooks, create alerts, and ensure it can be maintained by others. You think about the full lifecycle of systems, not just initial delivery.
• You have strong opinions, weakly held. You can make and defend architectural decisions, but you're open to feedback and willing to change course when presented with better information. You can disagree and commit.
• You understand that "building from scratch" doesn't mean rejecting existing tools—it means thoughtfully selecting, configuring, and integrating managed services and open-source solutions to create a cohesive platform. You know when to build and when to buy.
• You have experience making big changes to critical data infrastructure. You’ve successfully re-architected, migrated, or upgraded data tooling that has strict SLA’s, without significantly affecting downstream stakeholders.

Bonus points if:

• You have led a data infrastructure migration or modernization project where you defined the vision, approach, and implementation.
• You have created internal tools, frameworks, or CLIs that improved how teams work with data (not just one-off scripts).
• You have established data platform best practices like CI/CD workflows, testing frameworks, or observability standards where none existed.
• Expertise in cloud platforms and technologies analogous to our stack:
  • Our stack: GCP (BigQuery, Datastream, Cloud Functions, Vertex AI, GCS), dbt, Fivetran, Postgres, Python, Terraform, Looker, Retool
  • Analogous experience: AWS (Redshift, DMS, Lambda, SageMaker, S3) or Azure (Synapse, Data Factory, Functions), Snowflake, Airbyte/Stitch, infrastructure as code tools, BI platforms

WE OFFER 💫

• Health, Dental & Vision Plans
• Life Insurance
• Long/Short Term Disability
• Competitive Pay
• 401k Matching
• Team Member Stock Purchasing Program (TMSPP)
• Learning & Development Opportunities
• Tuition Reimbursement
• Unlimited PTO
• Daily Lunch, Snacks & Coffee (in-office only)
• Commuter benefits (in-office only)

Additional information: Salary range of $160,000 - $200,000 + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.

Rocket Money, Inc. is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

About the Role

Chime’s Data Platform team builds the infrastructure every engineering and analytics team depends on - ingestion, transformation, quality, governance, and self-serve tooling across batch and streaming workloads.

You’ll own core platform systems at scale, design the frameworks other teams build on, and set the technical standards for how data moves through Chime. High autonomy, real architectural trade-offs, production impact from day one. We’re hiring multiple engineers into this role at the senior level.

The base salary offered for this role and level of experience will begin at $187,000.00 and up to $259,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

• Design, build, and operate self-serve ETL/ELT frameworks supporting both batch and streaming workloads, with direct ownership of pipeline reliability, data quality SLAs, and schema evolution
• Drive the technical roadmap for our data platform - evaluate build-vs-buy decisions, define integration patterns, and set standards that engineering teams across the company adopt
• Partner with Product Engineering, Data Science, Analytics, and Marketing as a technical lead to design data contracts, onboard new data domains, and scale ingestion without sacrificing governance
• Architect and enforce data lineage, schema registry, and access controls across all domains - ensuring compliance with fintech regulatory requirements (SOX, PII handling)
• Own the platform - monitor, alert, debug, and resolve incidents across the data platform with the urgency expected of infrastructure that powers financial products
• Raise the technical bar of the team through code review, design reviews, and hands-on mentorship of junior and mid-level engineers
• Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary.

To thrive in this role, you have

• 5+ years building, shipping, and operating data infrastructure in production - not just writing pipelines, but owning their reliability, performance, and cost at scale
• Strong system design skills - you’ve written design docs, made trade-offs, and delivered the result
• Solid understanding of key metrics for data pipelines and experience building solutions to provide visibility to partner teams
• Deep proficiency in Python or Java/Kotlin, with strong opinions on testing, code quality, and maintainability in data-heavy codebases
• Production experience with the modern data stack, specifically:
• A cloud data warehouse (Snowflake, BigQuery, or Redshift)
• Workflow orchestration (Airflow, Dagster, or Prefect) and IaC (Terraform)
• At least one streaming technology (Kafka, Flink, or Kinesis) - you understand when batch isn’t enough
• Data modeling and transformation frameworks (dbt)
• Built or improved observability for data systems - freshness monitoring, row-level quality checks, schema drift detection, and SLA dashboards that engineering and business teams actually trust
• Experience operating in a regulated environment (fintech, healthtech, or similar) where data governance, access control, and audit trails are non-negotiable

#LI-GC1 #LI-Onsite

About the Role

As an Engineering Manager on Chime’s Data Platform, leading the Data Storage team, you will own the group that manages Chime’s online and analytical data stores and low-latency metric serving layer. Your team will be responsible for building and operating reliable, scalable, and secure storage foundations that power analytics, experimentation, and AI-driven product experiences across Chime.

You’ll partner closely with other Data Platform squads as well as Product Engineering, Security, and Analytics teams to define storage strategies, data contracts, and SLAs that support both high-scale batch workloads and latency-sensitive online use cases. Your leadership will directly impact how Chime stores, governs, and serves data - enabling trusted, self-serve, AI-ready data for Chimers across the company.

This role is not just about running infrastructure - it’s about setting a vision for the future of data storage at Chime, fostering a culture of technical excellence, and growing a high-performing team that can evolve our architecture as the business and our data scale.

The base salary offered for this role and level of experience will begin at $199,000 and up to $275,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

• Own the strategy and roadmap for Chime’s Data Storage Platform, including Snowflake, data lake and online data stores for low-latency access.
• Design and evolve scalable, high-performance storage architecture that balance reliability, cost, and ease of use for both analytical and in-product workloads.
• Ensure performant and secure data access by defining and enforcing access patterns, partitioning and clustering strategies, indexing, and caching and serving layers for key datasets and metrics.
• Collaborate across Data Platform and partner teams to define clear data contracts, schemas, and SLAs between producers, storage, and consumers.
• Build tooling and automation for governance and compliance across sinks (e.g., RBAC, PII protection, tokenization, lineage, and auditability) in partnership with Security, Risk, and Compliance.
• Manage and grow a team of engineers, setting clear expectations, providing coaching and feedback, and raising the bar on engineering quality and operational excellence.
• Establish strong operational practices, including on-call, incident management, postmortems, and SLOs for the storage and serving layers your team owns.
• Stay ahead of industry trends in data storage, lakehouse architectures, and AI/ML-ready data systems, and thoughtfully introduce technologies that improve our platform’s capabilities.

To thrive in this role, you have

• Have 8+ years of experience in high-scale, high-reliability software development, with a focus on platforms, infrastructure, and data storage systems.
• Have 3+ years of experience managing engineering teams, including hiring, performance management, and developing engineers.
• Have a track record of scaling products, platforms, and operations to support rapid growth in data volume, complexity, and criticality.
• Bring deep experience with data infrastructure components, such as data lakes and lakehouses (e.g., Iceberg), data warehouses (e.g., Snowflake), online and offline data stores, and both batch and real-time streaming systems.
• Have proven expertise in system and data architecture for scalable, secure, and cost-efficient data platforms, including schema design, data modeling, and partitioning strategies.
• Are comfortable working with modern data and infrastructure technologies, such as Spark, Flink, Kafka, Airflow, Kubernetes, and similar tools.
• Are proficient in Python or similar languages (e.g., Java, Scala) and familiar with SQL and performance tuning for analytical workloads.
• Have extensive experience in cloud-based data ecosystems, such as AWS (S3, DynamoDB, Redshift, Snowflake, EMR), GCP (BigQuery, Dataflow), or Azure equivalents.
• Understand data governance, security, and compliance best practices (e.g., RBAC, PII handling, auditability) and have helped design systems that meet regulatory and internal standards.
• Are deeply interested in the transformative potential of advanced AI systems and how to build AI-ready data foundations (metadata, lineage, semantic layers, feature and metric serving).
• Excel at building strong relationships with stakeholders across engineering, product, analytics, security, and finance, and can translate between technical and business contexts.
• Demonstrate strong people leadership, with a track record of building a culture of belonging and engineering excellence.

#LI-Hybrid #LI-GC1

Location: United States (remote)

What is Verse? 

Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.

Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.

The Role

You will be a member of the technical staff designing, building, and maintaining the next generation of data platform tools, pipelines, and orchestration frameworks to support multiple teams and products across a diverse range of data at Verse. This role supports Core Engineering needs within the organization and builds on top of existing engineering foundations focused on data. As a technical leader with advanced data engineering expertise, teammates will look to you to vet proposals, solutions to internal and customer-facing problems, system designs, and drive the implementation of these solutions with highest standards of software-engineering best practices. You will be an integral part of scaling our data platform as the company grows.

Key Responsibilities

• Ensure data quality, contracts and integrity with best practices around access, governance, and federation throughout the data lifecycle
• Implement, maintain, and promote best practices and hygiene in our dataland code repository for others to follow and emulate
• Write shared libraries and reusable data tools across a variety of data flows, sources, and sinks
• Partnering closely with our Data Science and data-heavy internal teams to support various analytical and AI/ML workflows
• Foster a culture and mindset of well-designed systems, test-driven software, and proactive communication with a high degree of transparency, mutual respect, and consideration for teammates
• Participate in code reviews, maintain technical documentation, and adhere to best software development practices

What We're Looking For (Minimum Qualifications)

• Advanced software development skills in Python, Rust, Java, Scala, or similar data-oriented language ecosystems
• Deep understanding of databases, data {lake,ware}house architectures, and data pipeline solutions across heterogeneous data and workloads in cloud-native environments
• Proficiency in carefully handling large, complex data and processing them (streaming and batch) in both transactional and analytical settings
• Commitment to delivering high quality software on time or ahead of schedule while adhering to best software development practices
• Continuous obsession for staying informed on contemporary technologies, tools, libraries, services, frameworks, or breakthroughs that could benefit the team
• Discipline using generative AI tools in day-to-day work

What Will Make You Standout (Preferred Qualifications)

• Bachelor’s  or master's degree in Computer Science, Data Science, or a related field
• Senior level software development talent and up
• Proven track record being a technical leader in high-performing data engineering teams
• Intimate knowledge of scaling “big data” solutions in cloud-based environments
• Hands on experience deploying and maintaining software such as Hadoop, Spark, Airflow, DBT, Dagster, Temporal, Presto/Trino, Iceberg, AlloyDB, Postgres, HBase, BigQuery, BigTable, Fabric, Hive, RedShift, S3, GCS, etc.
• Experience building event-driven architectures with streaming tools such as Kafka, NATS, GCP Pub/Sub, Kinesis, Bufstream, Flink, Beam
• Knowledge of managed or hosted data solutions such as Databricks, Snowflake, ClickHouse, Tinybird, etc
• Practical knowledge working with data in formats like Parquet, Avro, Protobuf, time series, text, image, video
• Working closely to support AI/ML-focused teams (knowledge of MLflow and Ray is a big a plus)
• Comfort building internal dashboards and data-focused visualizations

What Makes Verse a Great Place to Work? 

• Lead with Empathy: We lift each other up with humility and kindness, always putting colleagues and customers first
• Be Honest & Transparent: We prioritize effective communication to build trust with our team, customers, and stakeholders
• Move with Balance & Precision: We believe speed and perseverance must be accompanied by thoughtfulness and reflection
• Leave the World a Better Place: We are passionate about our mission, and we strive to create a sustainable world for future generations

Base Pay Range

$180,000 - $250,000+

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

Benefits and Employee Perks 

• Competitive compensation and equity grant at a high-growth start up 
• Comprehensive benefits package including medical, dental and vision insurance, and 401k 
• Flexible hours and unlimited PTO 
• Diverse and inclusive working environment 

Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.

The Core Services team within Snorkel AI's Infrastructure organization will own the data platform that powers everything at Snorkel — the pipelines, access layers, event systems, governance, and compute infrastructure that every product team and customer deployment depends on. We are a small team with a large surface area, and we are in the middle of a foundational architecture shift: moving from a single-database data path to a multi-source, event-driven platform with dedicated stores for different workloads (transactional data in Postgres/RDS, analytical data in Snowflake, bulk storage in S3, metrics platform). The decisions being made now will define how data flows at Snorkel for years. You will be making them.

You’ll also shape our AI-native development workflow, contribute in modernizing CI/CD workflow (Buildkite, GitHub Actions), and integrate AI SRE tooling. Your work will directly accelerate developer velocity, reliability, and product quality across the company

What You'll Do

• Build and maintain the shared data access library and SDKs that Platform, Packaging, and Dataset API teams use to read from and write to multiple data sources (Snowflake, S3, RDS). Design interfaces that abstract source-level complexity while providing built-in auth, RBAC enforcement, pagination, and query governance.
• Design and implement event-driven data flows using event brokers,  CDC connectors, schema registry, event routing, dead letter queues. Make sure events flow reliably and failures are visible and recoverable.
• Build the systems that track how data moves through the platform (lineage), enforce who can access what (governance and RBAC), and log what happened (auditing). This includes PII handling, retention policy enforcement, and audit infrastructure for enterprise and federal compliance.
• Instrument the data platform with OpenTelemetry, define and monitor SLOs for query latency and pipeline success rates, and build alerting that catches issues before they become incidents. You will be on-call for the systems you build.
• Contribute to infrastructure cost visibility and optimization -  query cost estimation, workload right-sizing, and routing data to the most cost-effective storage tier for its access pattern.

What You'll Bring

• 4+ years building platform infrastructure, data infrastructure, data platforms, or backend systems with significant data components. You have built and operated pipelines, data access layers, or ETL/ELT systems in production.
• Strong proficiency in Python. Our stack is Python-heavy across Prefect, FastAPI, dbt, and the SDK layer.
• Hands-on experience with SQL and at least two of: Snowflake, Redshift, Postgres. You understand the performance characteristics of each and can write queries that don't bring down production.
• Experience with AWS — S3, RDS, EKS, EventBridge, IAM. Comfortable working in a Terraform-managed environment
• Experience with Kubernetes. Our workloads run on EKS and you will deploy, debug, and scale services on K8s.
• Familiarity with data orchestration tools (Prefect, Airflow, or Dagster) and transformation frameworks (dbt).
• Understanding of data governance concepts — RBAC, PII handling, audit logging, data lineage.
• Fluency with AI-assisted development tools (Claude Code, Cursor, or similar). This is a hard requirement — the team uses these tools daily and we expect engineers to leverage them for code generation, debugging, and investigation.

Nice to Have

• Experience building shared libraries or SDKs consumed by multiple teams — versioning, backwards compatibility, migration support.
• Experience with event-driven architectures — CDC, event buses, schema registries, at-least-once delivery semantics.
• Experience with OpenTelemetry, ClickHouse, or similar observability infrastructure.
• Prior work in regulated environments (SOC 2, FedRAMP, HIPAA) where compliance requirements shaped system design.
• Experience with Ray for distributed compute workloads.

About The Role

As our Staff Data Engineer, you will own and evolve the foundational data systems that power NexHealth’s analytics and unlock the next generation of customer-facing insights. This is a hands-on, high-ownership role that combines architectural influence with deep execution. We need to expand our data capabilities for scale and improve our daily operations and enable self-service. You will drive the transformation of our data infrastructure.

You will design data pipelines, refactor the warehouse architecture, and lay down the modeling foundations that enable trusted analytics across the company. This work directly supports our mission to become the API for healthcare. With access to a rich and growing corpus of medical data, you will help NexHealth become a leader in data strategy, intelligence, and customer enablement.

This role is ideal for a Staff-level engineer who has seen and built great data platforms, is not afraid of legacy, and thrives in environments where the vision is clear, the systems are evolving, and the company is depending on data to unlock its next stage of growth.

What You’ll Do

• Own the Data Platform
  • Lead the architectural evolution of our data warehouse, modeling layer, and pipeline structure
  • Refactor core data models to support fast, self-serve access and shared understanding across teams
  • Build reliable ingestion and transformation systems that abstract over messy or fragmented inputs
  • Take responsibility for the structure, reliability, and extensibility of our warehouse and modeling layers
  • Replace brittle vendor-based pipelines with scalable, maintainable ingestion and transformation infrastructure
  • Build in observability, alerting, and validation to ensure the platform can scale with confidence
• Drive Strategic Data Initiatives
  • Collaborate closely with Staff-level analysts, engineers, and data consumers to unblock their workflows and enable data insights.
  • Partner with software engineers to anticipate and manage upstream schema changes and database shifts
  • Define and enforce clear data contracts and interface boundaries
  • Shape how the company can eventually leverage data science, customer segmentation, and industry-wide insights

What You’ll Bring

• 7+ years of experience in data engineering or software engineering with a focus on building scalable, well-tested systems
• Advanced fluency in SQL and Python with strong instincts around modular modeling, optimization, and abstraction
• Experience building on top of a modern managed data warehouse such as Snowflake, BigQuery, or Redshift
• Proven history of taking ambiguous, fragmented data systems and turning them into reliable, documented, high-trust platforms
• Ability to operate independently at a Staff level with a high sense of ownership
• A background in strong engineering cultures or top-tier product environments where quality, velocity, and ownership coexist
• Passion for clarity, simplicity, and helping teams move faster without cutting corners

P-1011

Job Location: San Francisco Bay Area, CA 

As a Sr. Staff Technical Solutions Engineer and tech subject matter expert, you will partner closely with our Field and Engineering teams to deliver high-touch specialized support and tailored technical solutions for Databricks' largest and most strategic customers in the Digital Native Business (DNB) segment. In this customer-facing role, you will leverage your technical expertise in Apache Spark™ and other data technologies to triage and resolve complex product issues and unblock our customers’ most critical technical challenges. 

The Impact You Will Have

• Perform advanced Troubleshooting and Root Cause Analysis to resolve performance and reliability issues in Spark, SQL, Delta, Streaming, and Databricks runtime features using tools like Spark UI metrics, Mosaic AI Model Service, DAGs, and event logs.
• Discover requirements for continuous monitoring to detect early performance issues working with R&D and NOC teams to optimize the DNB customer environments. 
• Build Rapid POCs, Test/Deploy/Monitor the solutions built by Databricks Engineering to address customer challenges and showcase advanced Spark/ML/AI runtime capabilities aligned with their business goals.
• Develop comprehensive playbooks and maintain a knowledge base of common issues and solutions for Spark, ML, and AI workflows.
• Train customer engineering and business teams on best practices in performance tuning, debugging, and effectively leveraging Databricks Features.
• Pilot new best practices processes/ programs, champion process improvements, and collaborate with cross-functional teams to enhance the customer experience.
• Advocate for customers in business review meetings and maintain close relationships as a trusted advisor and primary technical point of contact.
• Collaborate onsite with Field Engineering, Sales, and Product teams during customer engagements and technical presentations to provide rapid solutions to production-impacting issues, demonstrating deep technical expertise and building strong customer trust.

What We Look For

• Technical Expertise in Big Data and Spark: 8–12 years of experience designing, building, and troubleshooting distributed computing applications, with 4+ years delivering production-scale Spark/ML/AI solutions using Python, Java, or Scala.
• Data Engineering Specialization: Hands-on expertise with Data Lakes, SQL-based databases, and Cloud-based Data Warehousing/ETL tools like Snowflake, Redshift, Bigquery, etc
• Advanced Tech Skills: Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimization, and memory management, with additional proficiency in AI ecosystems like Machine Learning, Deep Learning, and Generative AI.
• Cloud and CI/CD Skills: Practical experience with AWS, Azure, or GCP, coupled with expertise in building and managing CI/CD pipelines, monitoring, and alerting systems.
• Customer-Facing Experience: 3–5 years in customer-facing roles such as Technical Account Manager or Solutions Architect, demonstrating strong communication, relationship-building, and problem-solving skills.
• Advanced Proactive Problem Solving Skills: Proven ability to anticipate, identify, and mitigate risks while planning solutions for production challenges. Effectively use sound business judgment, risk avoidance and subject matter expert resources to coordinate team efforts to solve problems. 
• Collaboration and Leadership: Proven ability to work with cross-functional teams and senior leadership to address roadblocks, mitigate risks, and drive customer success while creating impactful documentation for self-service solutions.

We are not able to provide visa sponsorship (including H-1B, OPT, or other employment-based visas) for this position. Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. 

About the Role

Machine Learning is a cornerstone at Taskrabbit, and we're looking for a seasoned Senior Machine Learning Engineer to join our team and help shape the future of ML/AI at Taskrabbit. This is a unique, full-stack role for an individual who is passionate about the entire machine learning lifecycle—from initial research and model development to building the robust infrastructure required to deploy and scale your work.

As a Senior Machine Learning Engineer, you will tackle exciting challenges that directly impact how people discover and connect with home services on the Taskrabbit platform. You will play a crucial role in advancing our capabilities in areas like search ranking, content discovery, and recommender systems. You will collaborate closely with data scientists and other engineers to design and implement novel algorithms, and you will partner with software engineers to ensure the scalability, reliability, and optimization of our models in production.

What You'll Work On:

• Model Development & Research: Research, design, and implement machine learning models to solve key business problems in areas like search ranking, recommendations, and content discovery.
• End-to-End ML Lifecycle: Own the entire lifecycle of ML models, including feature engineering, training, evaluation, deployment, and monitoring.
• Infrastructure & Scalability: Build scalable and reliable ML infrastructure and data pipelines that support reproducible feature engineering and machine learning model deployment in real-time, near real-time, and batch processes.
• Performance & Quality: Build monitoring services to understand data quality and model performance of complex systems, and collaborate with engineering and science teams to optimize existing algorithms for training and evaluation.
• Software Engineering Excellence: Independently solve complex problems, write clean, efficient, and sustainable code, and actively participate in code reviews, documentation, and the full software engineering lifecycle.

Your Areas of Expertise:

We welcome applicants from a variety of backgrounds and experiences. Below gives you a sense of how we're thinking about what you'll need to be successful in the role.

• BS, MS, or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field.
• 3+ years of industry experience building and deploying high-quality, production-grade machine learning models and systems.
• Strong theoretical knowledge and hands-on experience in machine learning, particularly in areas like search, ranking, recommender systems, or NLP.
• Solid software engineering skills with proficiency in one or more programming languages, including Python.​​  The candidate should have experience with popular ML libraries like Scikit-learn, lightgbm, xgboost, TensorFlow, PyTorch, etc.
• Proficiency in SQL is also required for writing complex queries and transforming data.
• Experience building REST API-based services.
• Experience with modern data and ML technologies, such as Docker, Kubernetes, Kafka, Airflow, data warehouses (eg snowflake, redshift or BigQuery), and data lakes.  
• Familiarity with dbt (Data Build Tool) is a plus for transforming and testing data.
• Familiarity with tools for Infrastructure as Code, such as Terraform, and CI/CD pipelines.
• Excellent communication skills, with the ability to present complex findings and recommendations clearly to both technical and non-technical audiences.
• A passion for quickly learning new technologies and a drive to solve challenging problems.

Compensation & Benefits: 

At Taskrabbit, our approach to compensation is designed to be competitive, transparent, and equitable. Total compensation consists of base pay + bonus + benefits + perks. The base pay range for this position is $150,000 - $200,000. This range is representative of base pay only, and does not include any other total cash compensation amounts, such as company bonus or benefits. Final offer amounts may vary from the amounts listed above and will be determined by factors including, but not limited to, relevant experience, qualifications, geography, and level.

Tatari is on a mission to revolutionize TV advertising. Founded in 2016 to help transform the antiquated world of TV advertising through the intelligent application of AI and machine learning, Tatari helps some of the world’s fastest growing brands including Chime, Calm, Tecovas, Manscaped, Saatva, and Liquid I.V., reach their customers using linear and streaming TV ads. Our platform combines sophisticated media buying with proprietary analytics to turn TV advertising into an automated, digital-like experience, enabling businesses of any size to advertise on TV.

That approach has earned Tatari broad industry recognition, including being named Best CTV AdTech Platform in the 8th annual MarTech Breakthrough Awards, as well as honors from Digiday (Best Connected TV Platform), AdExchanger (Most Innovative TV Advertising Technology), and Business Insider (Hottest AdTech Companies). Tatari has also been recognized as the Best Place to Work by Inc. Magazine. Backed by an executive team of former founders and senior leaders from companies including Shazam, TrueCar, AdapTV, LiveRail, Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising enters its next major era.

We are looking for a Staff and a Senior Platform Engineer to join our Engineering team. You will collaborate closely with our application engineering, data science, and analytics teams to understand and manage our infrastructure needs. This is a great opportunity to flex your skills across operations, application & data infrastructure, security and performance. Working with a small team, you will help drive the goals and metrics for your area and contribute to technology and architecture decisions. Unlike a more narrowly specialized role, this job affords a lot of agency and the opportunity to work with users across a number of different disciplines.

Responsibilities

• Manage and support several customer facing applications and products
• Work to find ways to improve our application and system reliability across our infrastructure
• Participate in technical architecture discussions; deployment, security and availability strategies
• Collaborate with data scientists, engineers, and product managers to understand the company's infrastructure-related needs
• Manage and support back office and business intelligence systems, used across multiple departments and teams

Qualifications

• 5+ years of experience working in cloud-based infrastructure. (AWS preferred)
• Experience with Auto Scaling, CDNs, DNS, Load Balancers, Multi Region and Multi-Tenant Topologies, Proxy Servers, and WAFs
• Strong experience with Linux, shell/bash and Python scripting
• Experience with monitoring and logging tools. (DataDog, Kibana, or similar)
• Experience with containerization technologies. (Kubernetes, Docker, or similar)
• Experience with configuration management and provisioning tools. (Terraform preferred)
• Experience managing RDBMS. (Postgres/RDS, Redshift, or similar)
• Experience with ingestion and ETL. a plus
• Experience with streaming and big data processing (Kafka, Spark, or similar), a plus

Benefits

• Total compensation ($180,000 - $210,000)
• Equity compensation
• Health insurance coverage for you and your dependents
• 401K, FSA, and commuter benefits
• $150 monthly spending account
• $1,000 annual continued education benefit
• $500 WFH reimbursement
• Unlimited PTO and sick days
• Monthly Company Wellness Day Off
• Snacks, drinks, and catered lunches at the office
• Team building events 
• Hybrid RTO of 2 days per week. THIS IS AN IN-OFFICE POSITION

At Tatari, we believe in the importance of cultivating teams with diverse backgrounds and offering equal opportunities to all. We strive to create a welcoming, inclusive environment where every team member feels valued and diversity is celebrated.

#LI-HYBRID

Tatari is on a mission to revolutionize TV advertising. Founded in 2016 to help transform the antiquated world of TV advertising through the intelligent application of AI and machine learning, Tatari helps some of the world’s fastest growing brands including Chime, Calm, Tecovas, Manscaped, Saatva, and Liquid I.V., reach their customers using linear and streaming TV ads. Our platform combines sophisticated media buying with proprietary analytics to turn TV advertising into an automated, digital-like experience, enabling businesses of any size to advertise on TV.

That approach has earned Tatari broad industry recognition, including being named Best CTV AdTech Platform in the 8th annual MarTech Breakthrough Awards, as well as honors from Digiday (Best Connected TV Platform), AdExchanger (Most Innovative TV Advertising Technology), and Business Insider (Hottest AdTech Companies). Tatari has also been recognized as the Best Place to Work by Inc. Magazine. Backed by an executive team of former founders and senior leaders from companies including Shazam, TrueCar, AdapTV, LiveRail, Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising enters its next major era.

We are looking for a Staff and a Senior Platform Engineer to join our Engineering team. You will collaborate closely with our application engineering, data science, and analytics teams to understand and manage our infrastructure needs. This is a great opportunity to flex your skills across operations, application & data infrastructure, security and performance. Working with a small team, you will help drive the goals and metrics for your area and contribute to technology and architecture decisions. Unlike a more narrowly specialized role, this job affords a lot of agency and the opportunity to work with users across a number of different disciplines.

Responsibilities

• Manage and support several customer facing applications and products
• Work to find ways to improve our application and system reliability across our infrastructure
• Participate in technical architecture discussions; deployment, security and availability strategies
• Collaborate with data scientists, engineers, and product managers to understand the company's infrastructure-related needs
• Manage and support back office and business intelligence systems, used across multiple departments and teams

Qualifications

• 5+ years of experience working in cloud-based infrastructure. (AWS preferred)
• Experience with Auto Scaling, CDNs, DNS, Load Balancers, Multi Region and Multi-Tenant Topologies, Proxy Servers, and WAFs
• Strong experience with Linux, shell/bash and Python scripting
• Experience with monitoring and logging tools. (DataDog, Kibana, or similar)
• Experience with containerization technologies. (Kubernetes, Docker, or similar)
• Experience with configuration management and provisioning tools. (Terraform preferred)
• Experience managing RDBMS. (Postgres/RDS, Redshift, or similar)
• Experience with ingestion and ETL. a plus
• Experience with streaming and big data processing (Kafka, Spark, or similar), a plus

Benefits

• Total compensation ($180,000 - $210,000)
• Equity compensation
• Health insurance coverage for you and your dependents
• 401K, FSA, and commuter benefits
• $150 monthly spending account
• $1,000 annual continued education benefit
• $500 WFH reimbursement
• Unlimited PTO and sick days
• Monthly Company Wellness Day Off
• Snacks, drinks, and catered lunches at the office
• Team building events 
• Hybrid RTO of 2 days per week. THIS IS AN IN-OFFICE POSITION

At Tatari, we believe in the importance of cultivating teams with diverse backgrounds and offering equal opportunities to all. We strive to create a welcoming, inclusive environment where every team member feels valued and diversity is celebrated.

#LI-HYBRID

Tatari is on a mission to revolutionize TV advertising. Founded in 2016 to help transform the antiquated world of TV advertising through the intelligent application of AI and machine learning, Tatari helps some of the world’s fastest growing brands including Chime, Calm, Tecovas, Manscaped, Saatva, and Liquid I.V., reach their customers using linear and streaming TV ads. Our platform combines sophisticated media buying with proprietary analytics to turn TV advertising into an automated, digital-like experience, enabling businesses of any size to advertise on TV.

That approach has earned Tatari broad industry recognition, including being named Best CTV AdTech Platform in the 8th annual MarTech Breakthrough Awards, as well as honors from Digiday (Best Connected TV Platform), AdExchanger (Most Innovative TV Advertising Technology), and Business Insider (Hottest AdTech Companies). Tatari has also been recognized as the Best Place to Work by Inc. Magazine. Backed by an executive team of former founders and senior leaders from companies including Shazam, TrueCar, AdapTV, LiveRail, Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising enters its next major era.

We are looking for a Staff and a Senior Platform Engineer to join our Engineering team. You will collaborate closely with our application engineering, data science, and analytics teams to understand and manage our infrastructure needs. This is a great opportunity to flex your skills across operations, application & data infrastructure, security and performance. Working with a small team, you will help drive the goals and metrics for your area and contribute to technology and architecture decisions. Unlike a more narrowly specialized role, this job affords a lot of agency and the opportunity to work with users across a number of different disciplines.

Responsibilities

• Manage and support several customer facing applications and products
• Work to find ways to improve our application and system reliability across our infrastructure
• Participate in technical architecture discussions; deployment, security and availability strategies
• Collaborate with data scientists, engineers, and product managers to understand the company's infrastructure-related needs
• Manage and support back office and business intelligence systems, used across multiple departments and teams

Qualifications

• 5+ years of experience working in cloud-based infrastructure. (AWS preferred)
• Experience with Auto Scaling, CDNs, DNS, Load Balancers, Multi Region and Multi-Tenant Topologies, Proxy Servers, and WAFs
• Strong experience with Linux, shell/bash and Python scripting
• Experience with monitoring and logging tools. (DataDog, Kibana, or similar)
• Experience with containerization technologies. (Kubernetes, Docker, or similar)
• Experience with configuration management and provisioning tools. (Terraform preferred)
• Experience managing RDBMS. (Postgres/RDS, Redshift, or similar)
• Experience with ingestion and ETL. a plus
• Experience with streaming and big data processing (Kafka, Spark, or similar), a plus

Benefits

• Total compensation ($180,000 - $210,000)
• Equity compensation
• Health insurance coverage for you and your dependents
• 401K, FSA, and commuter benefits
• $150 monthly spending account
• $1,000 annual continued education benefit
• $500 WFH reimbursement
• Unlimited PTO and sick days
• Monthly Company Wellness Day Off
• Snacks, drinks, and catered lunches at the office
• Team building events 
• Hybrid RTO of 2 days per week. THIS IS AN IN-OFFICE POSITION

At Tatari, we believe in the importance of cultivating teams with diverse backgrounds and offering equal opportunities to all. We strive to create a welcoming, inclusive environment where every team member feels valued and diversity is celebrated.

#LI-HYBRID

About the Role

You.com is a search platform serving millions of queries across consumer and enterprise products. That scale generates a lot of data: search quality signals, API usage logs, click behavior, billing events, and user engagement across the product. This role is responsible for building the analytics infrastructure that makes all of it useful.

You’ll own the dbt layer that transforms raw search logs, API events, and revenue data into clean, governed models. You’ll also build the dashboards that teams rely on to understand search performance, product engagement, and business health. Strong technical depth and strong visual judgment are both expected.

You’ll work closely with Finance, GTM, Product, and Engineering to define metrics, agree on how success is measured, and build the self-service infrastructure that reduces the analytics backlog for everyone.

Responsibilities

Data Modeling & Infrastructure

• Design and build core data models covering product usage, revenue, GTM performance, API consumption, and cost data
• Own the dbt project: architecture, documentation, testing, and CI/CD
• Build and maintain pipelines from source systems (Salesforce, billing, product events, API logs) into clean analytics layers
• Define and enforce modeling standards, naming conventions, and governance practices that hold up as the company scales
• Partner with Data and Backend Engineering to instrument key events and maintain data quality upstream

Dashboards & Reporting

• Build dashboards that give leadership and cross-functional teams clear, real-time visibility into business health
• Develop reporting across GTM, finance, product, and customer success
• Create self-service analytics that allow teams to answer their own questions without a backlog request
• Translate complex, multi-source analyses into clean outputs for executive audiences

Cross-Functional Partnership

• Partner with Finance on revenue accounting, COGS, and margin reporting
• Collaborate with GTM and Sales leaders on seller productivity, pipeline health, and marketing ROI dashboards
• Work with Product to define and track north-star metrics, funnel performance, and user behavior
• Serve as a trusted partner when teams need to agree on how something is measured

Data Quality & Governance

• Implement data quality monitoring so issues are caught before they reach stakeholders
• Maintain a documented data catalog that makes the warehouse accessible and understandable across the company
• Design reporting systems that support financial and operational audit requirements

Qualifications

• 5+ years of experience in analytics engineering, data engineering, or senior-level data analysis at a fast-growing company
• Strong, production-grade SQL skills; complex queries should be second nature
• Hands-on experience with dbt (Core or Cloud), including project structure, testing, and documentation
• Experience with a modern cloud data warehouse: Snowflake, BigQuery, or Redshift
• Demonstrated ability to build polished dashboards and reports in Looker, Tableau, or a comparable BI tool
• Experience building data models across GTM, finance, or product analytics domains
• Comfortable with Python for data transformation, scripting, or pipeline work
• Strong communication skills with the ability to present clearly to senior stakeholders and simplify complex analyses
• Bonus: experience at an AI-native company, familiarity with LLM-assisted analytics workflows, or prior work with usage-based or API-driven billing data

Staff Architect  

Role Overview 

We’re looking for a Staff Architect to lead architecture and technical delivery for a major domain within 6sense’s Revenue Intelligence platform (e.g., real-time signals ingestion & processing, ML inference/serving, multi-tenant data isolation, or GTM integrations & activation). 

This is a senior individual contributor role focused on high-leverage system design + execution leadership: driving architecture for complex initiatives, partnering closely with engineering and product leaders, and ensuring solutions are scalable, resilient, secure, and operable. You will be hands-on where it matters—through reference implementations, prototypes, and deep technical guidance that helps teams ship. 

Key Responsibilities 

Domain Architecture Ownership 

• Own the architecture for a core domain of the platform, ensuring it meets scalability, reliability, security, and performance requirements. 

• Drive end-to-end design for cross-service initiatives: clarify requirements, propose options, lead tradeoffs, and align stakeholders. 

• Produce high-quality design artifacts (HLDs, LLDs, data flow diagrams, API contracts) and lead design reviews. 

Delivery Enablement (Hands-on Leadership) 

• Provide hands-on technical leadership through reference implementations, prototypes/POCs, and critical-path contributions when needed. 

• Partner with engineering teams to translate architecture into executable plans (milestones, risks, dependencies, rollout strategy). 

• Help teams build “operable” systems: instrumentation, alerting, runbooks, dashboards, and failure-mode thinking. 

Data & Signal Processing (if domain-aligned) 

• Lead architecture for ingestion/enrichment pipelines handling large-scale behavioral events and third-party data. 

• Drive improvements to data quality, lineage, observability, and freshness SLAs. 

AI/ML Serving (if domain-aligned) 

• Guide architecture for feature pipelines and inference serving (batch and online), model monitoring, experimentation, and safe rollouts. 

• Partner with data science and ML engineering to productionize reliable, scalable ML systems. 

Multi-Tenant & Platform Foundations (if domain-aligned) 

• Drive patterns for tenant isolation, tenant-aware configuration, partitioning strategy, and scalable onboarding. 

• Identify and mitigate risks around compliance, data integrity, and access control. 

Integration & Activation  

• Lead architecture for integrations with CRM/MAP/GTM tools (Salesforce, HubSpot, Marketo, Outreach, etc.). 

• Establish patterns for reliable data activation (idempotency, retries, backfills, versioning, and extensibility). 

Engineering Excellence & Mentorship 

• Raise the bar through design reviews, technical mentorship, and knowledge-sharing. 

• Contribute to architecture standards and reusable patterns; participate in architecture forums/councils. 

• Identify architectural risks early and drive mitigation plans. 

 Required Qualifications 

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. 

• 8+ years in software engineering with significant focus on distributed systems and system design   

• Demonstrated experience designing and delivering data-intensive, distributed, cloud-based systems. 

• Strong understanding of:  

• Distributed systems, reliability, scalability, fault tolerance 

• Microservices/event-driven architectures 

• API design, data modeling, integration patterns 

• Observability and operability (metrics/logging/tracing, incident learnings) 

• Experience with a major cloud platform (AWS, GCP, or Azure). 

• Ability to influence across teams through clear communication, strong design rationale, and pragmatic decision-making. 

 Preferred Qualifications 

• Experience in B2B SaaS, MarTech/AdTech/Revenue Tech, or similar data-heavy product environments. 

• Experience with streaming/batch data systems (Kafka/Flink/Spark or equivalents). 

• Familiarity with OLAP/analytics stores (ClickHouse/Redshift/BigQuery/Druid/Trino, etc.). 

• Familiarity with ML platform concepts (feature pipelines, inference patterns, monitoring), even if not a full-time ML practitioner. 

• Experience designing multi-tenant data and service architectures. 

What Success Looks Like 

• A well-defined domain architecture that enables teams to ship confidently and operate reliably in production. 

• Reduced latency/freshness gaps, improved reliability/SLOs, and improved cost-to-serve within your domain. 

• Faster onboarding of new data sources/integrations or faster rollout of new AI-driven capabilities (depending on domain). 

• Strong cross-team alignment, fewer architectural surprises, and smoother delivery of major initiatives. 

 Why 6sense 

You’ll work on systems that directly shape how B2B revenue teams find and win customers—at massive data scale, with real-time signals, ML-driven predictions, and deep integrations across the GTM stack. 

Base Salary Range: $209,496.00 - $307,260.80. The base salary range represents the anticipated low and high end of the base salary range for this position. Actual salaries may vary and may be above or below the range based on various factors, including but not limited to work location and experience. The base salary is one component of 6sense’s total compensation package for this position. Other compensation may include a bonus program or commission plan, and stock options if approved by 6sense’s board. In addition, 6sense provides a variety of benefits, including generous health insurance coverage, life, and disability insurance, a 401K employer matching program, paid holidays, self-care days, and paid time off (PTO). #Li-remote

Notice of Collection and Use of Personal Information for California Residents: California Recruitment Privacy Notice and Policy

About Highnote 

Founded in 2020 by a team of leaders from Braintree, PayPal, and Lending Club, Highnote is an embedded finance company that sets the standard in modern card platform management. As an all-in-one card issuer processor and program management platform, we provide digital-first organizations with the flexibility to seamlessly issue and process payment cards, embed virtual and physical card payments, and integrate ledger and wallet functionalities—empowering businesses to drive growth and profitability.

We’ve raised $145M+ and have grown our team to 140+ employees. Headquartered in San Francisco, we’ve managed to build one of the most advanced payments teams in the industry, with team members in 25+ US states. 

Operating through our core values of customer obsession, executional excellence, intentional inclusion, we’re helping businesses grow for the future by creating the payment products demanded by tomorrow, with the ability to solve for use cases that don’t exist yet.

We are fast-moving, hands-on, and strongly believe everyone deserves a seat at the table. We believe we’re unlocking incredible opportunities that can change the future of payments, as long as we have the right people to make it happen.

Job Description

Core Services Team is responsible for building common application services and libraries, supporting application tooling needs and helping ensure the reliability, scalability and quality of the products.

What you’ll be doing

• Building secure and compliant platform products that solve customer needs
• Writing high quality and robustly tested code, mostly in Java
• Understanding customer problems to build the right solutions
• Documenting your work to support our rapidly-scaling company
• Interfacing with a variety of the company’s domains to strengthen our platform

What we are looking for

• 12+ years experience building production software systems
• A history of writing scalable, performant and maintainable code. We strongly believe languages can be learned and care more about your engineering skill over frameworks
• Experience building out common platform libraries such as logging, configuration, encryption, async etc
• Experience with Java, Spring Boot/Spring Framework, GCP services, and understanding of OAuth
• Proficiency using AI-powered development tools (e.g., Claude Code) across the full software development lifecycle - including design, prototyping, development, testing, and iteration. A demonstrated passion for AI-driven development, a commitment to continuously advancing AI skills, and a drive to push the boundaries of productivity and engineering outcomes.

Bonus skills

• Agentic AI experience
• Experience with cloud platforms such as GCP or AWS
• Experience with Spring Boot, Docker, and Kubernetes
• Knowledge of gRCP and Protobuf
• Experience with distributed event system
• Experience with software security
• Experience with big data technologies such as BigQuery and RedShift
• Experience with building data pipelines for search platform
• A background in the fintech space

Why Highnote?

• We’re a startup that allows for our employees to truly build from the ground up and impact every layer of our organization. 
• We’re a team of payments obsessed individuals. While some of us come from the fintech world, some of us don’t. We value the varied backgrounds and the diverse perspectives of our employees. 
• We’re small on hierarchy and big on growth. We’re a flat organization that allows everyone to have direct exposure to our leadership team. We are looking for builders who thrive in ambiguity. 
• We’re backed by Oak HC/FT, Costanoa Ventures, Adams Street Partners, Westcap, and Pinegrove Venture Partners. Angel Investors include Bill Ready (CEO at Pinterest) and Renaud Laplanche (Co-Founder & CEO of Upgrade).

Highnote benefits

• Flexible Paid Time Off
• 100% healthcare coverage + 75% coverage for dependents
• 401k program
• Paid Parental Leave: Up to 16 weeks paid leave for the birth parent, and up to 6 weeks paid leave for the non-birth parent
• Equity in Highnote
• Stipend to build out your home office; internet reimbursement
• At Highnote we have built a total rewards philosophy that includes fair, equitable, geo-based compensation that is performance and potential based. Our compensation packages are competitive based on robust market research and are a combination of a cash salary, equity, and benefits. In compliance with the Equal Pay for Equal Work Act, the annual salary range for applicants is $170,000-$230,000.

Please note that positions located in San Francisco are hybrid and include core working days of Monday, Tuesday, Wednesday, Thursday in office.  We provide flexible work options based on distance from our downtown SF office. Highnote believes in the power of face-to-face, personal connection. As a result, we prioritize in-person candidates.

Highnote is a diverse and inclusive company committed to growing a diverse and inclusive team. We invite people from all backgrounds and identities to apply. We do not discriminate based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other characteristics protected by US federal state or local laws, or the laws of the country or jurisdiction where you work. Additionally, we encourage everyone to share which pronouns you wish for us to use when addressing you (i.e.: she/her, he/him, they/them, etc).

About Highnote 

Founded in 2020 by a team of leaders from Braintree, PayPal, and Lending Club, Highnote is an embedded finance company that sets the standard in modern card platform management. As an all-in-one card issuer processor and program management platform, we provide digital-first organizations with the flexibility to seamlessly issue and process payment cards, embed virtual and physical card payments, and integrate ledger and wallet functionalities—empowering businesses to drive growth and profitability.

We’ve raised $145M+ and have grown our team to 140+ employees. Headquartered in San Francisco, we’ve managed to build one of the most advanced payments teams in the industry, with team members in 25+ US states. 

Operating through our core values of customer obsession, executional excellence, intentional inclusion, we’re helping businesses grow for the future by creating the payment products demanded by tomorrow, with the ability to solve for use cases that don’t exist yet.

We are fast-moving, hands-on, and strongly believe everyone deserves a seat at the table. We believe we’re unlocking incredible opportunities that can change the future of payments, as long as we have the right people to make it happen. 

What you’ll be doing

• Resolving core service performance issues at scale
• Building secure and compliant platform products that solve customer needs
• Writing high quality and robustly tested code, mostly in Java
• Understanding customer problems to build the right solutions
• Documenting your work to support our rapidly-scaling company
• Interfacing with a variety of the company’s domains to strengthen our platform

What we are looking for

• 8+ years experience building production software systems
• Expertise in threading, optimizations, performance tuning, and concurrency management
• Deep understanding of Java frameworks (including Spring), resiliency, and encryption libraries
• A history of writing scalable, performant and maintainable code. We strongly believe languages can be learned and care more about your engineering skill over frameworks 
• Excitement about shipping customer centric software
• Experience with Java >= 11, JPA ORM mapping, Crafting SQLs, unit and integration testing
• Proficiency using AI-powered development tools (e.g., Claude Code) across the full software development lifecycle - including design, prototyping, development, testing, and iteration. A demonstrated passion for AI-driven development, a commitment to continuously advancing AI skills, and a drive to push the boundaries of productivity and engineering outcomes.

Bonus skills

• Experience with cloud platforms such as GCP or AWS
• SpringBoot, Docker, and Kubernetes
• Experience with big data technologies such as BigQuery and RedShift
• Deep understanding of payment systems
• Experience building AI agents for financial or payment platforms
• Familiarity with AI agent frameworks (e.g., LangChain, CrewAI, or AutoGen)

Why Highnote?

• We’re a startup that allows for our employees to truly build from the ground up and impact every layer of our organization. 
• We’re a team of payments obsessed individuals. While some of us come from the fintech world, some of us don’t. We value the varied backgrounds and the diverse perspectives of our employees. 
• We’re small on hierarchy and big on growth. We’re a flat organization that allows everyone to have direct exposure to our leadership team. We are looking for builders who thrive in ambiguity. 
• We’re backed by Oak HC/FT, Costanoa Ventures, Adams Street Partners, Westcap, and Pinegrove Venture Partners. Angel Investors include Bill Ready (CEO at Pinterest) and Renaud Laplanche (Co-Founder & CEO of Upgrade).

Highnote benefits

• Flexible Paid Time Off 
• 100% healthcare coverage + 75% coverage for dependents
• 401k program
• Paid Parental Leave: Up to 16 weeks paid leave for the birth parent, and up to 6 weeks paid leave for the non-birth parent
• Equity in Highnote
• Stipend to build out your home office; internet and phone reimbursement
• At Highnote we have built a total rewards philosophy that includes fair, equitable, geo-based compensation that is performance and potential based. Our compensation packages are competitive based on robust market research and are a combination of a cash salary, equity, and benefits. In compliance with the Equal Pay for Equal Work Act, the annual salary range for applicants is $170,000-$230,000.

Please note that positions located in San Francisco are hybrid and include core working days of Monday, Tuesday, Wednesday, Thursday in office. We provide flexible work options based on distance from our downtown SF office. Highnote believes in the power of face-to-face, personal connection. As a result, we prioritize in-person candidates.  

Highnote is a diverse and inclusive company committed to growing a diverse and inclusive team. We invite people from all backgrounds and identities to apply. We do not discriminate based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other characteristics protected by US federal state or local laws, or the laws of the country or jurisdiction where you work. Additionally, we encourage everyone to share which pronouns you wish for us to use when addressing you (i.e.: she/her, he/him, they/them, etc).

About Highnote 

Founded in 2020 by a team of leaders from Braintree, PayPal, and Lending Club, Highnote is an embedded finance company that sets the standard in modern card platform management. As an all-in-one card issuer processor and program management platform, we provide digital-first organizations with the flexibility to seamlessly issue and process payment cards, embed virtual and physical card payments, and integrate ledger and wallet functionalities—empowering businesses to drive growth and profitability.

We’ve raised $145M+ and have grown our team to 140+ employees. Headquartered in San Francisco, we’ve managed to build one of the most advanced payments teams in the industry, with team members in 25+ US states. 

Operating through our core values of customer obsession, executional excellence, intentional inclusion, we’re helping businesses grow for the future by creating the payment products demanded by tomorrow, with the ability to solve for use cases that don’t exist yet.

We are fast-moving, hands-on, and strongly believe everyone deserves a seat at the table. We believe we’re unlocking incredible opportunities that can change the future of payments, as long as we have the right people to make it happen.

What you’ll be doing

• Building secure and compliant platform products that solve customer needs
• Writing high quality and robustly tested code, mostly in Java
• Understanding customer problems to build the right solutions
• Documenting your work to support our rapidly-scaling company
• Interfacing with a variety of the company’s domains to strengthen our platform

What we are looking for

• 12+ years experience building production software systems
• A history of writing scalable, performant and maintainable code. We strongly believe languages can be learned and care more about your engineering skill over frameworks 
• Excitement about shipping customer centric software
• Experience with Java >= 11, JPA ORM mapping, Crafting SQLs, unit and integration testing
• Proficiency using AI-powered development tools (e.g., Claude Code) across the full software development lifecycle - including design, prototyping, development, testing, and iteration. A demonstrated passion for AI-driven development, a commitment to continuously advancing AI skills, and a drive to push the boundaries of productivity and engineering outcomes.

Bonus skills

• Experience contributing to Card Acquiring platforms
• Experience with cloud platforms such as GCP or AWS
• SpringBoot, Docker, and Kubernetes
• Experience with big data technologies such as BigQuery and RedShift
• A background in the fin-tech space
• Experience building AI agents for financial or payment platforms
• Familiarity with AI agent frameworks (e.g., LangChain, CrewAI, or AutoGen)

Why Highnote?

• We’re a startup that allows for our employees to truly build from the ground up and impact every layer of our organization. 
• We’re a team of payments obsessed individuals. While some of us come from the fintech world, some of us don’t. We value the varied backgrounds and the diverse perspectives of our employees. 
• We’re small on hierarchy and big on growth. We’re a flat organization that allows everyone to have direct exposure to our leadership team. We are looking for builders who thrive in ambiguity. 
• We’re backed by Oak HC/FT, Costanoa Ventures, Adams Street Partners, Westcap, and Pinegrove Venture Partners. Angel Investors include Bill Ready (CEO at Pinterest) and Renaud Laplanche (Co-Founder & CEO of Upgrade).

Highnote benefits

• Flexible Paid Time Off
• 100% healthcare coverage + 75% coverage for dependents
• 401k program
• Paid Parental Leave: Up to 16 weeks paid leave for the birth parent, and up to 6 weeks paid leave for the non-birth parent
• Equity in Highnote
• Stipend to build out your home office; internet reimbursement
• At Highnote we have built a total rewards philosophy that includes fair, equitable, geo-based compensation that is performance and potential based. Our compensation packages are competitive based on robust market research and are a combination of a cash salary, equity, and benefits. In compliance with the Equal Pay for Equal Work Act, the annual salary range for applicants is $190,000-$240,000.

Please note that positions located in San Francisco are hybrid and include core working days of Monday, Tuesday, Wednesday, Thursday in office.  We provide flexible work options based on distance from our downtown SF office. Highnote believes in the power of face-to-face, personal connection. As a result, we prioritize in-person candidates.

Highnote is a diverse and inclusive company committed to growing a diverse and inclusive team. We invite people from all backgrounds and identities to apply. We do not discriminate based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other characteristics protected by US federal state or local laws, or the laws of the country or jurisdiction where you work. Additionally, we encourage everyone to share which pronouns you wish for us to use when addressing you (i.e.: she/her, he/him, they/them, etc).

Philo: a streaming service for TV and movie lovers

At Philo, we’re a group of technology and product people who set out to build the future of television, marrying the best in modern technology with the most compelling medium ever invented — in short, we’re building the TV experience that we’ve always wanted for ourselves. In practice this means leveraging cloud delivery, modern tech stacks, machine learning, and hand-crafted native app experiences on all of our platforms. We aim to deliver a rock solid experience on the streaming basics, while cooking up next generation multi-screen and multi-user playback.

Data at Philo

Data underpins everything we do at Philo: making informed business decisions; analyzing and improving the quality of our streaming experience; running product experiments to optimize our signup flows and improve user journeys; and making it effortless for our users to find the perfect thing to watch. Philo serves over a billion streams to its users every year, generating a wealth of data that we leverage at all levels of the organization. Philo’s data platform operates at very large scale, processing trillions of events annually in a petabyte-scale data lake and supporting thousands of data workflows and analytical queries that power decision-making across the company.

On the Data team, we’re looking for people who are comfortable working on a variety of interesting engagement, content discoverability, experimentation, acquisition, and retention-related data projects across our streaming service. You’ll be working closely with other data scientists, analysts, and engineers to build and deploy solutions directly for our service – this work spans both foundational data platform work like data warehouse architecture, metric governance, and semantic consistency across our entire data stack, as well as insights and modeling work that leverages the platform to deliver business value. In addition, you’ll work with stakeholders in other departments to understand our business needs, build highly reliable and accurate data pipelines that the company can trust, and deliver business-focused data insights to help the entire team thrive.

We are passionate about problem-solving and providing data-informed insights for the entire company, using both cutting-edge techniques and proven practices in close collaboration with every department. To complete our work we build on modern open-source tools including dbt, GrowthBook, Robyn, Superset, and PyTorch as well as SaaS tools such as Segment, Redshift, Snowflake, SageMaker, AWS Glue, Mode, Omni, Avo, and BigEye.

Some of the recent projects our Data Science team members have worked on include:

• Building marketing mix models and multi-touch attribution models to optimize customer lifetime value and predict RoAS (Return on Ad Spend)
• Modeling to determine which early product behaviors predict conversion
• Running experiments to evaluate and improve our ML-based content recommendation/personalization system
• Building data models for analysis of lifecycle marketing communications impact
• Modeling to analyze the impact of Quality of Experience events (e.g. rebuffering) on customer engagement and other business metrics.
• Data infrastructure engineering work including data warehouse cluster upgrades, per-query infra cost optimization, implementation of Apache Iceberg data storage, and evaluating alternative data warehouse technologies.
• Ongoing analytics engineering work to reliably and accurately model complex billing and subscription data, enabling it to be easily queried for business insights.
• Price sensitivity research and competitive market analyses

The role

Philo is seeking a Head of Data to lead and evolve our growing team of Data Scientists, Data Engineers, and Data Analysts – an effective, collaborative and empathetic leader who will help scale the team to meet our evolving data needs. This leader will work with stakeholders across the company to ensure that every department at Philo has the reliable and accurate data required to deliver the data-driven insights we need in order to achieve and exceed our goals as a company. 

Responsibilities

• Own all things data at Philo: ensure that stakeholders at Philo have access to the timely and accurate data driven insights that they need to do their jobs.
• Oversee the core data science work executed in cross-functional teams to drive product goals, including product experiments and A/B tests, Growth & Acquisition modeling, and product insights, including customer journey analysis and measuring effectiveness of content search and recommendation systems.
• Own the quality and performance of the data platform at Philo, including platform architecture and instrumentation, data collection/processing/validation, data governance, and security and compliance.
• Ensure that we are collecting the right data and events, processing them in a scalable and modular way, and building a foundation of reliable data that teams across the company can build insights from.
• Collaborate closely with the engineering team and AI/ML engineers to support the development and delivery of Philo’s content recommendation system.
• Collaborate closely with data roles in our business and finance teams (business insights, business analysts and financial analysts) to help them build a deep understanding of the Philo business, customers, and content trends.
• Manage the data team: train, mentor and coach members of the data team, direct their work and support their career growth; identify the roles we need as we grow and hire fantastic people to fill those roles.

Qualifications 

• 15+ years of experience across analytics, data science, data engineering, or related data functions, with significant proven experience leading multidisciplinary data teams through ambiguity, in both a strategy and personnel management capacity. (Startup experience preferred.)
• Strong skills as a hands-on data scientist who can lead by example, including demonstrated understanding of data architecture, statistical modeling in either Python or R (Python preferred), A/B/n experimentation practices, SQL, and experience independently developing data driven insights. Demonstrated ability to train and coach team members in these skills.
• Strong written and verbal communication skills; you are a strong communicator who can explain complex trends, data findings and analytical methodology to broad audiences with varying technical backgrounds.
• A deep understanding of business priorities and the ability to partner with both technical and non-technical stakeholders.
• Experience working in a fast-paced, high-growth startup environment (or ability to adapt to this environment very quickly).
• Experience in consumer subscription, streaming, media, ad-supported products, or other event-rich digital businesses is preferred.
• Experience with Machine Learning and Deep Learning is a strong plus.

More about Philo

At Philo, we’re a company that puts people first—both our subscribers and our team. We empower our colleagues to do their best work while supporting one another in pursuing shared goals. We value pragmatism, pride in our work, and passion, with transparency and openness as fundamental parts of our culture.

We’re committed to diversity, equity, inclusion, and accessibility as we grow the Philo team and shape the future of TV. We believe that a diverse range of voices and perspectives enables us to innovate faster and create the best experiences for our subscribers. Philo is proud to be an Equal Opportunity Employer. We’re committed to supporting every candidate and employee. If you need an accommodation at any stage of the process, please email recruiting@philo.com and we’ll work with you to meet your needs.

Philo offers 70+ top-rated networks, including AMC, BET, CMT, Comedy Central, Discovery Channel, Food Network, Hallmark Channel, HGTV, HISTORY, Investigation Discovery, Lifetime, MTV, Nickelodeon, OWN, VH1, We TV, and more. It also includes all the groundbreaking originals and blockbuster movies available with AMC+ and access to HBO Max Basic With Ads and discovery+. Our service also includes 100+ free channels and premium add-ons like STARZ and MGM+.

Our extensive library boasts over 85,000 titles, and our unlimited DVR allows users to save their favorite shows and movies for up to a year, skipping ads for a seamless viewing experience. Stream on up to three devices simultaneously, whether on your phone, tablet, laptop, or TV using Roku, Apple TV, Fire TV, Samsung TV, Android TV, Vizio TV, or Chromecast.

Philo is headquartered in San Francisco, with offices in New York City and Cambridge, MA. Our leadership team includes alums from HBO, Tubi, and Meraki, and is backed by NEA and industry partners like Warner Brothers Discovery, Viacom, AMC, and A&E.

Join us at Philo and be part of a team that's shaping the future of TV!

Status: Full-time
Location: San Francisco, CA or remote within the U.S.
Compensation: Includes annual salary, company stock options, and health benefits. Salary is determined by experience and location:

• San Francisco, New York City: $255K - $300K
• Boston, DC Metro, Los Angeles, Seattle: $240K - $285K
• Denver, Atlanta, Austin, Las Vegas, Sacramento, Chicago: $225K - $270K
• Texas, Florida: $215K - $260K

We value a diverse and inclusive workplace and we welcome people of different backgrounds, experiences, skills, and perspectives. Philo is an equal opportunity employer. We believe that everyone does their best work when they are supported by each other and the company, and we offer a generous set of benefits to make sure the Philo team is happy and healthy. Here is a sampling of the benefits we offer our team:

• Full health, dental and vision coverage for you and your family
• 401(k) plan with employer contributions (we match 100% of deferrals up to 3% of pay and 50% of the next 2% of pay)
• Flexible working hours
• Up to 20 weeks of fully paid parental leave
• Unlimited paid time off for vacation and sick leave
• $2,000 annual vacation bonus (we pay you to take a two week vacation)
• $5,250 annually for professional development and educational assistance
• $1,250 annual home office + TV stipend during first year of employment ($250 annually thereafter)
• $500/month ($6,000/year) bonus for employees who commit to working at least 3 days per week in our offices, plus generous commuter benefits ($315/month towards transit, rideshare, bike rental, or parking at our HQ office in San Francisco)
• Free Gympass subscription — an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps
• Dog-friendly office
• And much more!

For California Residents: Philo’s CCPA Notice at Collection – Employees, Applicants, Owners, Directors, Officers and Contractors

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Role

We are looking for a Senior Infrastructure Engineer to join our growing team where you will design and implement the infrastructure that powers the Peregrine platform.

As an engineering team, we believe empathy leads to better solutions. Seeing people use the product is a priority and helps us find the right answers. Engineers will have the opportunity to work closely with our team onsite to understand the diverse use cases Peregrine serves. We value strong ownership while fostering collaboration and continuous feedback.

As a Senior Infrastructure Engineer, you will leverage a variety of technologies to scale our platform, enabling secure connections to customer networks while managing terabytes of data. You will tackle a wide range of complex challenges, including:

• Building highly available and secure production systems
• Architecting scalable and secure network topologies
• Supporting the ingest engine for massive data processing
• Accelerating the entire engineering lifecycle

Our stack is constantly evolving but is built on AWS GovCloud, Kubernetes, Docker, Terraform, Pulumi, PostgreSQL, Redshift, Elasticsearch, and more.

About you

• Deep understanding of architecture and scaling for large-scale software systems
• Proven experience in building cloud-based network systems across diverse customer environments
• Extensive expertise in Platform Engineering, DevOps, or Site Reliability Engineering (SRE)
• Track record of successfully developing highly available and secure network systems for both production and customer environments
• Strong knowledge of platform, network, and data security, with experience in compliance controls and accreditations
• Solid foundation in database operations, with a strong preference for experience in PostgreSQL and Elasticsearch

What we look for

• 8+ years of experience building and maintaining complex infrastructure for web applications with strict uptime requirements
• Expertise in modern software development best practices, including deployments, CI/CD, data management, security, and distributed systems
• Extensive experience with AWS or other cloud platforms, leveraging containerization and orchestration technologies like Docker and Kubernetes
• Proficiency in software engineering, particularly in Python, for developing APIs and automation tools.
• Hands-on experience with Infrastructure as Code tools such as Terraform, CloudFormation, or Pulumi
• Strong background in Linux system administration, with proficiency in Python, Bash, or other scripting languages for automation
• Deep understanding of CI/CD tools, including GitHub Actions, GitLab CI, and ArgoCD
• Located in NYC and open to working in office

Salary Range: $170,000 - $250,000 Annually + Benefits + Equity (if applicable) + Bonus (if applicable)

Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, certifications or licenses, and specific work location. Information on the benefits offered is here.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Role

We are looking for a Senior Infrastructure Engineer to join our growing team where you will design and implement the infrastructure that powers the Peregrine platform.

As an engineering team, we believe empathy leads to better solutions. Seeing people use the product is a priority and helps us find the right answers. Engineers will have the opportunity to work closely with our team onsite to understand the diverse use cases Peregrine serves. We value strong ownership while fostering collaboration and continuous feedback.

As a Senior Infrastructure Engineer, you will leverage a variety of technologies to scale our platform, enabling secure connections to customer networks while managing terabytes of data. You will tackle a wide range of complex challenges, including:

• Building highly available and secure production systems
• Architecting scalable and secure network topologies
• Supporting the ingest engine for massive data processing
• Accelerating the entire engineering lifecycle

Our stack is constantly evolving but is built on AWS GovCloud, Kubernetes, Docker, Terraform, Pulumi, PostgreSQL, Redshift, Elasticsearch, and more.

About you

• Deep understanding of architecture and scaling for large-scale software systems
• Proven experience in building cloud-based network systems across diverse customer environments
• Extensive expertise in Platform Engineering, DevOps, or Site Reliability Engineering (SRE)
• Track record of successfully developing highly available and secure network systems for both production and customer environments
• Strong knowledge of platform, network, and data security, with experience in compliance controls and accreditations
• Solid foundation in database operations, with a strong preference for experience in PostgreSQL and Elasticsearch

What we look for

• 8+ years of experience building and maintaining complex infrastructure for web applications with strict uptime requirements
• Expertise in modern software development best practices, including deployments, CI/CD, data management, security, and distributed systems
• Extensive experience with AWS or other cloud platforms, leveraging containerization and orchestration technologies like Docker and Kubernetes
• Proficiency in software engineering, particularly in Python, for developing APIs and automation tools.
• Hands-on experience with Infrastructure as Code tools such as Terraform, CloudFormation, or Pulumi
• Strong background in Linux system administration, with proficiency in Python, Bash, or other scripting languages for automation
• Deep understanding of CI/CD tools, including GitHub Actions, GitLab CI, and ArgoCD
• Located in Washington, D.C. and open to working in office

Salary Range: $170,000 - $250,000 Annually + Benefits + Equity (if applicable) + Bonus (if applicable)

Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, certifications or licenses, and specific work location. Information on the benefits offered is here.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Role

We are looking for a Senior Infrastructure Engineer to join our growing team where you will design and implement the infrastructure that powers the Peregrine platform.

As an engineering team, we believe empathy leads to better solutions. Seeing people use the product is a priority and helps us find the right answers. Engineers will have the opportunity to work closely with our team onsite to understand the diverse use cases Peregrine serves. We value strong ownership while fostering collaboration and continuous feedback.

As a Senior Infrastructure Engineer, you will leverage a variety of technologies to scale our platform, enabling secure connections to customer networks while managing terabytes of data. You will tackle a wide range of complex challenges, including:

• Building highly available and secure production systems
• Architecting scalable and secure network topologies
• Supporting the ingest engine for massive data processing
• Accelerating the entire engineering lifecycle

Our stack is constantly evolving but is built on AWS GovCloud, Kubernetes, Docker, Terraform, Pulumi, PostgreSQL, Redshift, Elasticsearch, and more.

About you

• Deep understanding of architecture and scaling for large-scale software systems
• Proven experience in building cloud-based network systems across diverse customer environments
• Extensive expertise in Platform Engineering, DevOps, or Site Reliability Engineering (SRE)
• Track record of successfully developing highly available and secure network systems for both production and customer environments
• Strong knowledge of platform, network, and data security, with experience in compliance controls and accreditations
• Solid foundation in database operations, with a strong preference for experience in PostgreSQL and Elasticsearch

What we look for

• 8+ years of experience building and maintaining complex infrastructure for web applications with strict uptime requirements
• Expertise in modern software development best practices, including deployments, CI/CD, data management, security, and distributed systems
• Extensive experience with AWS or other cloud platforms, leveraging containerization and orchestration technologies like Docker and Kubernetes
• Proficiency in software engineering, particularly in Python, for developing APIs and automation tools.
• Hands-on experience with Infrastructure as Code tools such as Terraform, CloudFormation, or Pulumi
• Strong background in Linux system administration, with proficiency in Python, Bash, or other scripting languages for automation
• Deep understanding of CI/CD tools, including GitHub Actions, GitLab CI, and ArgoCD
• Located in San Francisco and open to working in office

Salary Range: $170,000 - $250,000 Annually + Benefits + Equity (if applicable) + Bonus (if applicable)

Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, certifications or licenses, and specific work location. Information on the benefits offered is here.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Reporting to the VP of Data Engineering and Analytics, this role is to lead the Data Analytics team to enable global Analytics across Oura.

About the Role

We are seeking an experienced analytics platform leader as the Director for the Data Analytics team.  In this role, you will be responsible for setting the vision and roadmap for the Analytics Data Lifecycle including Business Metrics, Business Glossary, Data Governance, Data Products to accelerate our business growth, deepen our product and membership understanding, and optimize our business operations.

The core function is to define and execute the organization’s data strategy to drive business decisions and outcomes by bridging the gap between technical and business stakeholders, transforming data into actionable insights to improve performance, efficiency and revenue.

You will lead a talented team of business and data analysts, acting as a player-coach to guide their work and develop their careers. As a key partner to leaders across the Data Engineering and Analytics organization, you will translate complex business challenges into a clear analytical roadmap, ensuring your team delivers accurate, trustworthy, and actionable insights that shape the future of Oura's growth.

What You Will Do

• Vision & roadmap for analytics: Define and execute the analytics data lifecycle (business metrics, KPI frameworks, data products, governance) tied to company OKRs and growth objectives.
• Strategic problem framing: Translate ambiguous, cross‑functional business problems into clear analytical roadmaps and prioritised portfolios of work. 
• Executive communication & storytelling: Convert complex data into clear, actionable insights for senior stakeholders across Finance, Marketing, Sales, Product, Hardware/Supply Chain, Membership, Commercial, CX, Clinical, etc. 
• Collaboration: Independently collaborate with different stakeholders including Data Management, Data Engineering, Data Scientists, Research Operations, Testing, Software, Firmware, and Hardware to define and implement improvements and new functionality and support internal Data lakehouse consumers in their day-to-day work.
• Cross‑functional influence: Serve as a trusted advisor to business and technical leaders; drive alignment and adoption of analytics standards, metrics, and tools across domains.
• People leadership: Build, lead, and develop high‑performing analytics teams (including managing managers), acting as a player‑coach and fostering technical excellence and business impact.
• Data Products: Enable the creation of a unified data catalog. Design, visualize and manage data domains to enable the creation of interoperable, trustworthy data products that can be easily consumed by other domains, often through data pipelines and stores like data lakes or lakehouses. 

• Self-Serve Platform Analytics Platform: Develop and maintain both prepared and self-serve data infrastructure platforms that provide domain teams with the tools and capabilities to create, manage, and consume data products.  Use of AI Agents to deliver interactive dashboards with automated insights, predictive analytics, and anomaly detection 
• Global Data Governance, Residency, Data Mesh Privacy: Ensure that our federated data governance of the data mesh and processes meet privacy, compliance, and security requirements.
• Establish scalable data management and governance frameworks that uphold data quality and integrity in line with industry best practices across multiple regions internationally
• Translate complex data into clear, actionable insights for stakeholders at all levels. 
• Data Literacy:  Enable global KPI metrics dashboard with a governed data dictionary to enable self service
• Champion best practices in data management of the global unified data mesh to ensure the accuracy, reliability, and trustworthiness of all data 

What You Have

• 10+ years of leadership in data/analytics; built high‑performing teams and cloud data platforms; 5+ years managing managers and scaling teams.
• Proven ability to lead the data lifecycle from definition through delivery; Master & Reference Data Management (MDM/RDM) expertise.
• Hands‑on leadership of data mesh delivery, management, and governance.
• Track record building scalable governance frameworks that uphold data quality and integrity.
• Experience building a data‑driven culture and self‑service decision‑making; delivering measurable business outcomes and actionable insights; passion for data literacy.
• Experience innovating with emerging data technologies; attracting, developing, and inspiring top data talent.
• Proficiency with Analytics tools such as Tableau, ThoughtSpot, Looker, SQL, workflow engines, and stream processing.
• Hands‑on familiarity with AWS/GCP/Azure and Databricks / BigQuery / Redshift.
• Cross-Functional Collaboration: Experience working closely with the other leaders to ensure a holistic view of the customer journey from purchase to support. Partner with Business Domain Owners, Data Engineering, Data Science and Business teams to advocate for the unified data analytics and data governance best practices to succeed.
• Build, operate, and improve Oura’s Data lakehouse: Experience building and working with of a global data technology and platform that unifies data across systems to move, process, and store large amounts of data (Terabyte–Petabyte scale) leveraging tools such as Google Big Query, VertexAI, Databricks, Azure, AWS, S3, Spark / Glue, Athena, dbt, Iceberg, Snowflake, Docker, workflow engines, and more.
• Experience applying AI/ML and predictive analytics to drive efficiency, personalization, and growth. Specifically, AI/LLM Enablement and Readiness: Natural Language Processing (NLP) and Large Language Model (LLM) Design using Retrieval Augmented Generation (RAG), Vector based data architecture and design, Prompt Engineering to enable LLM reporting
• Experience leading data mesh delivery, management and governance
• Establish scalable data management and governance frameworks that uphold data quality and integrity in line with industry best practices. 
• Experience leveraging AI, machine learning, and predictive analytics to enhance efficiency, personalization, and business growth 
• Familiarity with some of the following: Tableau, Thoughtspot, Looker, Workflow engines, Stream processing, MLops, Spark, Athena, SQL, dbt, Databricks, Agentic AI.
• You are self-motivated, proactive, and able to lead and manage your own work effectively
• A pragmatic and goal oriented approach to development

Nice to Have

• Experience in the healthcare, wellness, consumer electronics, wearables, digital health, or subscription services industries.
• Data and Platform Architecture, Agentic AI and ML Ops platform experience
• Security & compliance - determined to establish excellent HIPAA, PHI, GDPR,  Healthcare data governance, privacy, and compliance standards in regulated environments
• Familiarity and experience with the Data Mesh architecture
• Broad knowledge of software fundamentals, databases, warehouses, and system design with experience on various programming languages
• Hands-on expertise in cloud platforms (AWS, GCP, or Azure), data mesh (Databricks, BigQuery or Redshift), and modern architectures 
• Experience streamlining multiple data pipelines into a centralized function that allows effective and efficient oversight of business processes and product development; expertise in integrating diverse data sources, including product, transactional, and compliance data
• Embedded analytics into product, finance, sales, marketing, business operations, and customer experience 
• Ability to navigate hypergrowth while managing regulatory constraints 
• Strong people leader, capable of both strategic leadership and driving execution; experience leading and scaling data and analytics teams north of 10 
• Strong technical foundation, demonstrated through education or early-career hands-on roles 
• Experience with production-quality AI/ML, predictive modeling, and leveraging analytics tools like VertexAI, MLOps, MLFlow, dbt, Microstrategy, Tableau, and Power BI, Thoughtspot 
• Experience leading the development of a robust and scalable data platform that can support the organization’s growing data needs 
• Advanced degree in Engineering, Data Science, Statistics, Computer Science, or a related field is preferred 

Benefits 

At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.

What we offer:

• Competitive salary and equity packages
• Health, dental, vision insurance, and mental health resources
• An Oura Ring of your own plus employee discounts for friends & family
• 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
• Paid sick leave and parental leave

Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Region 1 $226,100 - $266,000

We are not considering candidates residing in the following states: Alaska (AK), Delaware (DE), Iowa (IA), Mississippi (MS), Missouri (MO), Nebraska (NE), South Dakota (SD), West Virginia (WV), and Wisconsin (WI)