[Hiring] Staff Data Engineer @Consumer Edge

Role Description

We’re hiring a Staff Data Engineer to set the technical direction for identity and audience data in our data products. You’ll design how our data connects across sources and partners, and build the pipelines our data products depend on, working with data science, product, and fellow engineers.

• Own identity data.
• Design identity data models and matching logic, and keep them accurate, auditable, and current.
• Build partner data mappings.
• Build and maintain identifier mappings with external partners, and report match quality and coverage.
• Build data pipelines.
• Build and run the production pipelines behind our data products.
• Build privacy in.
• Build consent, opt-out, deletion, and access controls into identity data, working with legal and security.
• Set the quality bar.
• Create data quality frameworks, monitoring, and anomaly detection for pipelines that carry billions of rows.
• 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.

Qualifications

• 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.
• Hands-on identity resolution experience, such as entity resolution or match tables, and familiarity with common ad tech identifiers.
• Experience with advertising data.
• Expert SQL and Python, with deep BigQuery or Snowflake experience and a modern stack such as dbt and Airflow.
• 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 Codex as an everyday part of your work.

Requirements

• Data clean room experience (nice to have).
• Streaming pipelines with Kafka or Pub/Sub (nice to have).
• Building AI developer tooling: agent harnesses, MCP servers, evals, or CI guardrails (nice to have).
• Background in ad tech, martech, or consumer data products (nice to have).
• Experience building for privacy and governance: consent, opt-outs, deletion, and state privacy laws (nice to have).

Benefits

• Competitive compensation.
• Company equity.
• 401(k) matching.
• Work-from-home flexibility.
• Subsidized health benefits.
• Performance-based bonus opportunity.
• Paid parental leave.
• Flexible and generous time off.