Data Engineering Manager

The role

You will own the data transformation layer and warehouse, including the dbt layer and metric definitions. You will lead a new Data sub-team in Platform Engineering as a hands-on player-manager.

What you will do

• Own the data layer and implement metric definitions in dbt.
• Run the transformation layer and warehouse.
• Set direction for warehouse strategy, ClickHouse, and API/MCP exposure.
• Hire a Data Engineer and a Senior Data Scientist.
• Set the team charter and run delivery, quality, and on-call health.
• Set agentic engineering practice using AI agents.
• Stay hands-on by reading, reviewing, and writing SQL, dbt, and Python.

Required qualifications

• 7+ years in data/analytics engineering.
• 2+ years managing a small team (2-5).
• Track record of hiring and developing ICs.
• 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.
• Has owned a warehouse or pipeline budget and reduced it with measurable results.
• Translates business needs into a technical plan and sequences a backlog.
• Has owned data accountability for finance, operations, and go-to-market stakeholders.
• Understands B2B SaaS metrics (ARR, ACV, gross margin, on-time delivery).
• Uses AI tools daily and knows where they help, mislead, and need verification.
• Documents decisions clearly and communicates tradeoffs, risk, and cost to leadership.

Nice to have

• Stood up a data function from zero, or revived an abandoned one.
• Run dbt in production at scale on BigQuery.
• Operated ClickHouse.
• Shipped analytics that runs in both cloud and self-hosted environments.

About the company

LILT is a machine learning company that uses AI, machine translation, and human-in-the-loop expertise to translate content. The company aims to make the world's information accessible to everyone regardless of language.