Lead Data Engineer - Identity

Role Description

Identity is central to how AdTech works today: advertisers want cross-surface reach, user-level measurement, and lower-funnel attribution. Their data reaches us two ways, and each has a clear next step:

• Direct onboarding currently runs on a partner's identity spine and we want to build a new, multi-source graph of our own.
• DMP feeds are proven and now need to scale as we enter in-app inventory.

In this role you'll own the graph, a standardized ingestion path that stands up each new feed faster and cheaper than the last, and the audience state and reporting behind self-serve discovery. You'll also set the technical bar for the engineers building it with you.

The Daily To-Do

• Build a new identity graph:
  • Take stock of what we have today, set its direction, and sequence the rollout: identifier sync, translation, clustering (with Data Science), opt-out handling.
• Standardize partner and client onboarding across web, CTV and mobile identifiers, including cleanroom onboarding, so each new feed costs less to stand up than the last.
• Ready the identity audience data layer for self-serve: creation, activation, state, and the reporting clients will discover audiences through.
• Own and raise the bar on the domain's observability and alert response:
  • Inventory today's signals, monitors and alerts, centralize them, and bring each to standard: a freshness and quality commitment, context for AI-assisted triage, and a runbook.
• Lead and grow the domain's data engineers:
  • Define the standards for testability, cost efficiency and the patterns worth repeating, then raise the team to them through your own code, reviews, and knowledge-sharing, recording decisions in ADRs.

Qualifications

• You've designed and owned large-scale, interdependent data systems, including at least one you built from scratch, and you turn ambiguity into a sequenced roadmap with Product and Data Partnerships.
• You've led engineers, setting direction, reviewing work, developing people, while staying hands-on.
• You have mastery of Python, Airflow and Spark, and write transformations that are idiomatic, testable and tuned for cost and performance; you write SQL for Snowflake with the same discipline.
• You're at home in AWS and Kubernetes, can read infrastructure logs to diagnose failures and slowness, and have worked with third-party APIs inside ingestion pipelines.
• You're fluent with AI tooling in your own work, and you think about what makes a codebase legible to it.

Requirements

• Strongly Preferred:
  • Identity resolution or graph work in AdTech: matching, device and household graphs.
  • Privacy and consent obligations: opt-outs, deletion, GDPR and CCPA.
  • Data cleanrooms for partner or client onboarding.
  • CI/CD with GitHub Actions/ArgoCD; monitoring with VictoriaMetrics/Prometheus/Grafana.
• Nice To Have:
  • Iceberg or a comparable table format at production scale.
  • Streaming or near-real-time processing (Kafka, Redpanda or similar).
  • Low-latency stores such as Aerospike.
  • Experience with OLAP databases like Clickhouse.

Benefits

• AdAge Best Places to Work
• ThinkLA Partner of the Year
• Built In Best Places to Work
• Cynopsis 2025 Top Women in Media - Jeannine Shao Collins
• Martech Breakthrough Awards - Best Overall Adtech Company
• Digiday Media Awards Best Event
• Cynopsis Media Impact Awards-Best CTV Platform
• Martech Breakthrough Awards-CTV Innovation
• Adweek Media Plan of the Year Awards - Best Use of Insights