Data Engineering Lead - Ad-Tech Analytics Platform

About the role

Trillion is looking for a hands-on data engineering leader to own its ad-tech analytics and reporting platform and manage the engineers who build it. The role is a player-coach position with direct reports: setting technical direction, coaching the team and owning delivery, while still writing production code and solving difficult data problems. The first priority is keeping the current legacy pipeline stable while designing and building its replacement. Working hours span the United States and Australia, so regular overlap with both time zones is needed.

Key responsibilities

• Set technical direction for the ad-tech data platform, centered on Kafka and ClickHouse
• Design, build and operate high-volume ETL/ELT pipelines ingesting ad, traffic and application events from real-time streams and legacy sources
• Maintain the existing pipeline and reporting while leading a phased replacement of the legacy architecture
• Build and maintain a canonical event model and efficient roll-up tables for analytics, Metabase and applications
• Develop minute-level and near-real-time aggregations, including deterministic reprocessing and backfills
• Write and review production code for pipelines, Kafka consumers and producers, schema migrations and operational tooling
• Define standards for ClickHouse schema, partitioning, sharding, replication, retention and query performance
• Review application logging and instrumentation, and introduce parallel event publishing where needed
• Establish standards for testing, monitoring, documentation, data quality and service levels
• Manage the data engineers through one-to-ones, coaching, goals and feedback, and grow the team
• Turn business and reporting needs into technical designs and milestones, and investigate discrepancies affecting revenue, optimization or customer reporting
• Partner with Product, Engineering, Analytics and leadership on monetization and reporting requirements, metric definitions and Metabase data models

Required profile

• 6+ years building and operating production data systems, including high-volume event data and near-real-time pipelines
• Experience directly managing data engineers while staying hands-on in production systems
• Working knowledge of the ad-tech ecosystem (requests, impressions, clicks, conversions, attribution, CPM/RPM/CTR)
• Solid grasp of data modeling and distributed system trade-offs
• Experience shipping pipelines with CI/CD, orchestration, observability and safe backfill or reprocessing
• Able to read application code to improve event schemas, logging and instrumentation

Required skills

• ClickHouse or a comparable columnar OLAP database (direct ClickHouse experience strongly preferred)
• Kafka, including event design, producers and consumers, delivery semantics, replay and troubleshooting
• Advanced SQL and analytical and time-series query patterns
• Helpful: ClickHouse cluster tuning, Flink or Spark Structured Streaming, data observability frameworks, data science or ML for optimization

What we offer

• Flexible remote work, with optional in-office days
• Health coverage and a 401(k) match
• A collaborative environment with room to shape the platform and team
• Lead-level scope with direct reports; title and salary agreed based on experience