Data Tech Lead

About the role

Marsh is looking for a hands-on Data Tech Lead in its Innovation & Data Office (IDO) in Chicago. You will lead a squad of 4-8 data engineers (employees and contractors) and also build things yourself: whiteboarding data models, pairing with engineers on pipelines and presenting delivery plans to business stakeholders. The first assignment is likely in a Mercer business (Wealth or Careers), but the expectation is fungibility across domains.

Key responsibilities

• Run a delivery pod of 4-8 data engineers, set technical direction, decompose work, manage sprint execution and be accountable for what the squad ships.
• Write code, build pipelines, debug production issues and step in when things are broken.
• Design data models, medallion architectures, ingestion contracts and reusable patterns, with attention to schema evolution, data quality, idempotency and lineage.
• Work with Engagement Leads and business stakeholders to turn business needs into data solutions and push back when requests don't make technical sense.
• Bring CI/CD, version control, testing, code review and documentation to the squad, and focus on developer experience and operational excellence.
• Use the Databricks stack (Unity Catalog, Delta Lake, Spark) on AWS and Azure, with infrastructure-as-code, Git workflows and pipeline orchestration.

Required profile

• 5+ years of hands-on data engineering experience, including some time leading or mentoring engineers.
• Ability to lead a mixed team of employees and contractors, setting expectations and building cohesion.
• Fluency with Git, CI/CD, automated testing, infrastructure-as-code and DataOps.
• Intellectual curiosity about the business domain and clear communication with both business leaders and engineers.

Required skills

• Strong, recent proficiency in SQL, Python and Spark.
• Cloud data platforms: Databricks strongly preferred; Snowflake, Synapse or similar accepted.
• Nice to have: Databricks-specific experience, dbt or similar transformation frameworks, data governance patterns, document or unstructured data ingestion pipelines, and exposure to LLM-based tooling or analytics engineering.

The applicable base salary range is $139,000 to $277,900, depending on experience, skills, location and other factors. Marsh is committed to hybrid work, with at least three days per week in the office or onsite with clients.