Remote

Lead the technical direction for audience data products and build high-volume pipelines for audience creation, partner data onboarding, identity mapping, and external data delivery. Mentor engineers, oversee design reviews and build-versus-buy decisions, and develop AI-enabled engineering tooling with appropriate guardrails. Collaborate with data science, product, engineering, and external partners., We’re hiring a Staff Data Engineer to set the technical direction for our audience data products and build and run the pipelines behind them, from build to delivery, working alongside data science, product, and fellow engineers. What you’ll do

• Build audience pipelines. Create, size, refresh, and deduplicate audiences, with clear contracts on what each one contains.
• Onboard partner data. Build repeatable patterns for bringing in partner data.
• Keep partner data mappings current. Maintain identifier mappings with partners as they change, and track match quality over time.
• Deliver to partners. Deliver data to external partners through APIs, files, and data shares, with tracking, retries, and alerting.
• Set technical direction. Lead design reviews and build-versus-buy decisions, and mentor data engineers through design and code reviews.
• Lead how the team builds with AI. Work AI-first every day, and build the agent harnesses, shared skills, and guardrails that make AI-generated work safe to ship., Own the architecture and technical direction of scalable data platforms, including Python pipelines, Airflow orchestration, Snowflake, Databricks, and AWS systems. Establish standards for reliability, testing, governance, security, monitoring, and data delivery. Lead complex incident resolution, cost optimization, design reviews, and platform decisions while partnering cross-functionally. Mentor engineers, influence roadmaps, reduce technical debt, and support hiring and organizational development. Top Skills: AirflowAmazon S3SparkAWSCi/CdData CatalogingData LineageDatabricksDatadogDbtKafkaLaunchdarklyMongoDBPii MaskingPostgresPythonRbacSegmentSnowflakeSQLTableau Capital One

• 8+ years in data engineering or backend data systems, including production pipelines on high-volume data (consumer data is a plus)
• Ad tech or martech experience with identity and audience data
• Experience delivering data to external partners on a schedule
• Expert SQL and Python, and deep experience with BigQuery or Snowflake
• Production experience with dbt and Airflow (or a similar orchestrator), CI/CD, and infrastructure as code
• A track record of setting technical direction across teams, and clear communication with engineers and business leaders
• Comfort using AI coding tools such as Claude Code, Cursor, or GitHub Copilot as an everyday part of your work

Nice to have

• Integrations with ad tech platforms
• Data clean room experience
• Building AI developer tooling: agent harnesses, MCP servers, evals, or CI guardrails
• Background in ad tech, martech, or consumer data products
• Experience handling personal data under privacy rules: hashing, consent, opt-outs, and deletion

We offer competitive compensation, company equity, 401(k) matching, work-from-home flexibility, and subsidized health benefits. Compensation and Benefits

The annual base salary for this role is between $175,000 - $210,000, depending on experience, with the opportunity for a performance-based bonus, company equity, 401(k) matching, paid parental leave, flexible and generous time off, work-from-home flexibility, and subsidized health benefits., Remote United States 175K-210K Annually Senior level 175K-210K Annually Senior level Database Lead the technical direction for identity and audience data systems. Design identity models, partner mappings, high-volume production pipelines, privacy controls, data quality frameworks, monitoring, and anomaly detection. Collaborate with data science, product, legal, security, and engineering teams while mentoring engineers and leading design reviews. Develop AI-enabled engineering tools and guardrails, and ensure reliable, auditable data products at scale. Top Skills: AirflowBigQueryClaude CodeCodexCursorDbtKafkaMcp ServersPub/SubPythonSnowflakeSQL, Fanatics, One Month Ago Remote or Hybrid 286K-392K Annually Senior level 286K-392K Annually Senior level Fintech * Machine Learning * Payments * Software * Financial Services Leads enterprise data engineering strategy and architecture for pipelines, external data sharing, and scalable data platforms. Designs and codes critical data solutions while driving adoption of modern technologies, governance, resiliency, operational excellence, and unified data architecture. Advises stakeholders, mentors engineers, recruits talent, evaluates emerging data and AI technologies, and develops platform roadmaps. The role requires hands-on expertise across AWS, lakehouse architecture, streaming, distributed computing, data warehousing, and multiple programming languages. Top Skills: AgileAirflowAmazon RedshiftApache FlinkSparkAWSAws GlueCassandraDagsterDatabricksDynamoDBEmrJavaKafkaLakehouseMongoDBMonte CarloPythonScalaSnowflakeSplunkSQL

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Join a dynamic team that’s redefining consumer data analytics. Consumer Edge (“CE”) is a leading data and insights-as-a-service (IaaS) company specializing in the global consumer, B2B, and healthcare economies. CE delivers real-time, transaction-based intelligence enriched by deep industry expertise. Its solutions equip corporate and investment leaders with best-in-class tools for strategic decision-making, offering granular insights and benchmarking across products, brands, sub-industries, and industries. CE’s unique capabilities turn complex data into clear, actionable insights that drive smarter, faster decisions., At Consumer Edge, you’ll join a high-performance team at the forefront of data-driven decision-making for the world’s leading investors and brands. You’ll have the opportunity to shape an important growth market, work alongside smart and ambitious colleagues, and directly influence how we scale internationally.