Data Engineering Manager: Build & Lead Core Data Layer

Lilt; Washington, Northern (IN, KY); Hybrid; USD 140,000 - 200,000; Full time

Job summary

LILT is seeking a Data Engineering Lead to own the transformation layer and warehouse, ensuring consistent metrics across Analytics and internal dashboards. You will manage a Data sub-team, hire key roles, and set the charter for delivery, quality, and on-call health.

You will directly influence platform strategy and cost management while hands-on with SQL, dbt, and Python to deliver reliable data for product, finance, and go-to-market decisions.

Qualifications

• 7+ years in data/analytics engineering, including 2+ years managing a small team (2-5).
• Experience owning data warehouse budgets and driving cost-down initiatives.
• Strong SQL and Python production pipelines; hands-on with dbt or equivalent.

Responsibilities

• Own the data layer: implement every metric definition once in dbt; ensure consistency across dashboards and reports.
• Run the transformation layer and warehouse with clear ownership, tests, and cost tracking; drive cost-down.
• Set warehouse strategy, define API/MCP exposure, and back decisions with written cases.
• Build and lead the Data sub-team: hire a Data Engineer and a Senior Data Scientist; oversee delivery, quality, and on-call health.
• Define AI agentic practices for building, testing, and reviewing pipelines and models.

Skills

SQL

Python

dbt

BigQuery

Data modeling

Team leadership

Go-to-market metrics

Education

Bachelor's degree in CS/Data/Math

Tools

dbt

BigQuery

ClickHouse

Snowflake

Python

Argo Workflows

Kubernetes

Job description

LILT is seeking a Data Engineering Lead to own the transformation layer and warehouse, ensuring consistent metrics across Analytics and internal dashboards. You will manage a Data sub-team, hire key roles, and set the charter for delivery, quality, and on-call health.

You will directly influence platform strategy and cost management while hands-on with SQL, dbt, and Python to deliver reliable data for product, finance, and go-to-market decisions.