Lead Data Engineer

We're hiring a Data Engineering Lead to help scale and guide a growing team of data engineers. This role is ideal for someone who enjoys solving technical challenges hands-on while also shaping engineering best practices, coaching others, and helping cross-functional teams deliver data products with clarity and speed. You'll manage a small team of ICs responsible for building and maintaining pipelines that support reporting, analytics, and machine learning use cases. You'll be expected to drive engineering excellence from code quality to deployment hygiene and play a key role in sprint planning, architectural discussions, and stakeholder collaboration. This is a critical leadership role as our data organization expands to meet growing demand across media performance, optimization, customer insights, and advanced analytics.

Responsibilities:

• 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.

Requirements:

• 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).
• Exposure to BI tools like Tableau or Looker.
• Experience collaborating with data scientists on ML workflows and experimentation platforms.
• Knowledge of data contracts, schema versioning, or platform ownership patterns.