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Data Engineering Manager

Lilt

Skills

Required

  • transformation layer
  • data / analytics
  • SQL
  • Python
  • BigQuery
  • ClickHouse
  • hiring and developing ICs
  • production pipelines
  • Snowflake
  • has owned data accountability
  • AI

Join LILT as a Data Engineering Manager, where you will own the data transformation layer and warehouse, lead a new Data sub-team, and ensure consistency in metric definitions across various teams. You will also have the opportunity to build your team, set direction for the data layer, and stay hands-on with SQL, dbt, and Python. Enjoy benefits such as medical coverage, a monthly lifestyle stipend, paid parental leave, and meaningful equity.

Ownership of LILT's data transformation layer, including the dbt layer and warehouse, ensuring consistency in metric definitions.

Leading a new Data sub-team in Platform Engineering, hiring and growing a Data Engineer and Senior Data Scientist, and making decisions regarding the transformation layer and warehouse.

Responsibilities

  • Settling discrepancies in metrics across Finance, Operations, Production, and Product, ensuring trust in the numbers reported.
  • Cost and roadmap ownership: has owned a warehouse or pipeline budget and reduced it with measurable results; translates business needs into a technical plan and sequences a backlog against limited headcount

Requirements

  • People management: 7+ years in data/analytics engineering, including 2+ years managing a small team (2-5), with a track record of hiring and developing ICs
  • Hands-on fundamentals: fluent in SQL and Python; has built and run production pipelines and a dbt (or equivalent) transformation layer; comfortable with BigQuery, ClickHouse, Snowflake, or similar
  • Stakeholder and business metrics: has owned data accountability for finance, operations, and go-to-market stakeholders, and understands B2B SaaS metrics (ARR, ACV, gross margin, on-time delivery) and how definition drift breaks them
  • Effective AI use and communication: uses AI tools daily and knows where they help, mislead, and need verification; documents decisions clearly and communicates tradeoffs, risk, and cost crisply to leadership
  • Stood up a data function from zero, or revived an abandoned one
  • Shipped analytics that runs in both cloud and self-hosted environments
  • Run dbt in production at scale on BigQuery; operated ClickHouse

Pay

USD 170,000 - 205,000