Team Lead Data Engineering

We are seeking a Team Lead, Data Engineering to lead a squad of Data Engineers while remaining deeply involved in the technical delivery of enterprise data solutions. This is a true player-coach opportunity for a senior data engineering professional who enjoys both coding and people leadership.

You will be responsible for the delivery, reliability, and engineering quality of critical data pipelines and data products, while mentoring and developing a team of engineers. The ideal candidate will bring strong expertise in modern data platforms, cloud-based data warehousing, ELT/ETL architecture, and Agile delivery practices.

Key Responsibilities Lead a team of Data Engineers and provide coaching, mentoring, performance feedback, and career development.

Design, build, optimize, and support scalable data pipelines using modern data stack technologies.

Own end-to-end delivery of data engineering initiatives from requirements through production support.

Establish and enforce engineering best practices including code reviews, testing, CI/CD, documentation, and version control.

Drive operational excellence through monitoring, troubleshooting, root cause analysis, and incident reduction.

Implement automated data quality validation frameworks and data observability practices.

Partner with business stakeholders, analysts, scientists, and product teams to translate requirements into technical solutions.

Ensure compliance with data governance, security, privacy, and regulatory requirements.

Optimize data platform performance, scalability, and cost efficiency.

Lead Agile ceremonies and communicate delivery status, risks, and mitigation plans.

Required Qualifications Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.

7+ years of Data Engineering and/or Software Engineering experience.

1+ years of leadership experience as a Team Lead, Technical Lead, or Squad Lead.

Strong hands‑on experience with: Snowflake, dbt, Fivetran (or equivalent ingestion platform), SQL, Python.

Experience building and supporting production‑grade data pipelines.

Knowledge of data modeling, ELT/ETL frameworks, CI/CD, DataOps, and Agile methodologies.

Experience implementing data quality and testing frameworks.

Strong stakeholder management and communication skills.

Preferred Experience Life Sciences, Pharmaceutical, Healthcare, or other regulated industry experience.

Collibra, Alation, Microsoft Purview, or data catalog tools.

Airflow, Kafka, streaming, or near real‑time data architectures.

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