Job Description

What you//'ll do Lead and grow a team of data engineers working across ETL/ELT, data warehousing, and ML-enablement Own team delivery across sprints, including planning, prioritization, QA, and stakeholder communication Set and enforce strong engineering practices around code reviews, testing, observability, and documentation Collaborate cross-functionally with Analytics, BI, Revenue Operations, and business stakeholders in Marketing and Sales Guide technical architecture decisions for our pipelines on GCP (BigQuery, GCS, Composer) Model and transform data using dbt and SQL, supporting reporting, attribution, and optimization needs Ensure data security, compliance, and scalability - especially around first-party customer data Mentor junior engineers through code reviews, pairing, and technical roadmap discussions What You Bring 6+ years of experience in data engineering, including 2+ years of people management or formal team leadership Strong technical background with Python, Spark, Kafka, and orchestration tools like Airflow Deep experience working in GCP, especially BigQuery, GCS, and Composer Strong SQL skills and familiarity with DBT for modeling and documentation Clear understanding of data privacy and governance, including how to safely manage and segment first-party data Experience working in agile environments, including sprint planning and ticket scoping Excellent communication skills and proven ability to work cross-functionally across global teams. Nice to have Experience leading data engineering teams in digital media or performance marketing environments Familiarity with data from Google Ads, Meta, TikTok, Taboola, Outbrain, and Google Analytics (GA4)