Lead Data Engineer (Contract, Remote)

We are hiring a hands-on Lead Data Engineer for one of our US-based clients, an established product company running a modern cloud data platform. Trusted, traceable data drives the decisions their platform makes every day, and this role owns the data foundation behind it.

This is a build-and-lead role, not a manage-from-a-distance role. You will design and build pipelines, write and review SQL and Python, tighten orchestration, chase down production data issues, and set direction for a small data team (4 to 6 people). If your idea of a lead is someone who has stopped touching code, this is not the role for you.

What you will actually do:

• Design, build, review and support production data pipelines and data models
• Write and review SQL, Python, transformation logic and data quality checks
• Improve orchestration so workflows are observable, restartable and easy to operate at 2am
• Set up practical data validation, reconciliation and lineage so bad data gets caught early, not fixed downstream
• Partner directly with the client's CTO on durable data architecture and honest build-versus-simplify calls
• Coach a lean team and reduce the "only one person knows how this works" problem

The stack:

Snowflake, dbt, Airflow, Python, SQL, Tableau. Running on AWS (RDS, EKS, SQS, Redis/ElastiCache, S3). Application side is Java/Spring Boot with GitHub, Jira, Confluence and modern CI/CD. You do not need every single tool, but you must be genuinely strong in a Snowflake, dbt, Airflow, Python, SQL and AWS world.

What we are looking for:

• 8+ years hands-on in data engineering, data platform or analytics engineering
• Real depth in SQL, Python, data modelling and pipeline development
• Proven experience building, debugging and supporting production data workflows in the cloud
• Solid grip on data quality, validation, monitoring and production support
• Enough leadership weight to earn trust from engineers in architecture and code reviews
• Comfortable in a lean, fast-moving company where leaders stay close to the work

Nice to have: experience with large-scale operational and analytics data; experience in a compliance-aware or regulated environment (SOC 2, data privacy, auditability, secure access); DataOps, data contracts, schema evolution; experience working with offshore or contractor teams.