Lead Data Engineer (#5552)

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Lead and mentor a team of data engineers, providing technical direction as well as people leadership.
Partner with business stakeholders and senior analysts to gather requirements and translate business KPIs and OKRs into data models and pipelines.
Design, build, and maintain scalable data models that support marketplace analytics, including web/app tracking and marketing use cases.
Write and optimize complex SQL to transform and model data for analytics consumption.
Build and troubleshoot code-based data pipelines using Python, Spark, and Airflow, jumping in hands-on when needed while guiding the wider engineering team's pipeline work.

Proven experience leading a data engineering team — this role requires genuine people leadership, not just senior-level technical skills.
Strong ownership mindset, with a track record of delivering reliably on time while minimizing tech debt and redundancy and adhering to best practices and standards.
5+ years of hands-on experience in Data Engineering.
Hands-on experience building data pipelines with Python and Spark — the project's pipelines are code-based (not SQL/dbt-based) — with the ability to jump in and contribute directly when needed, as well as a deep enough understanding to follow and guide what other engineers on the team are building.
Hands-on experience with Airflow for orchestrating data pipelines.

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