Engineering Manager

About the role

This is a Data Engineering Manager opportunity with a growing New York AI platform for consumer packaged goods brands, running deductions, cash application, planning and finance in one system. The role builds the data team from a single senior analytics engineer. Note that this is a CPG finance business, not healthtech. You’ll manage and develop the team, make major decisions on warehouse design, pipelines, orchestration and tooling, hire data engineers, and set standards for modelling, testing, documentation, monitoring and on-call. You’ll own numbers and pipeline failures and stay hands-on writing SQL, building models and reviewing PRs, particularly early on. The tools are Snowflake, dbt, Airflow, Dagster or similar. The ideal candidate will have 7+ years in data or analytics engineering, at least 2 years managing engineers, and experience building a data warehouse from an early or messy state. Strong SQL and data modelling and production ETL/ELT experience are expected. This is a New York City role with relocation support. We're looking for someone curious, pragmatic, and eager to work across the stack with a small senior team. You'll own end-to-end delivery of major features, influence architecture, and mentor engineers.

What you'll do

• Ship customer-facing features on a weekly cadence.
• Partner with design and product on scoping and trade-offs.
• Drive technical quality through review, testing, and docs.
• Mentor one or two engineers on your team.

Requirements