Lead Data Engineer - Identity
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Role details
Tech stack
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Job description
- 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., * 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.
Requirements
Techies who want to build the future. Creatives who want to design it better. Communicators to win business. Collaborators to build it. Data pros who turn numbers into insights. Product builders who turn ideas into innovations. Anyone eager to be on a team that doesn’t stop to ask what’s next, because they’re already building it., * 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., * 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 & conditions
- 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
About the company
Kargo creates powerful moments of connection between brands and consumers to build businesses. Every day, our 600+ employees work to radically raise the bar on what agentic AI, CTV, eCommerce, social, and mobile can do to deliver unique ad experiences across the world’s most premium platforms. Taking a creative science approach to all we do, we continuously innovate solutions that outperform industry benchmarks and client expectations. Now 20+ years strong, Kargo has offices in NYC, Chicago, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland.
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