Technical Lead, Data

Marsh McLennan•Boston, MA

1d•Hybrid

About The Position

This is a hands-on leadership role where you will lead a squad of data engineers and also build things yourself. You will own technical delivery for priority initiatives within Marsh’s Innovation & Data Office (IDO). Your first assignment will likely be in one of our Mercer businesses (Wealth or Careers), but the expectation is fungibility, not permanent domain alignment. As IDO's priorities evolve, so will yours. The constant is the quality of your engineering leadership, not the label on the work. Your squad will be a mix of employees and contractors, and you'll be responsible for making that team perform as a unit: setting standards, unblocking problems, mentoring engineers, and holding the bar on quality. The work lands in Databricks. The outcomes land in the business. This is a hands-on technical leadership role where managing people is one of the things you do, alongside designing architecture, writing code, reviewing PRs, and solving hard data problems. If your last few years have been spent in meetings about data rather than working with data, this isn't the right fit.

Requirements

5+ years of hands-on data engineering experience
At least some time leading or mentoring other engineers
Strong proficiency in SQL, Python, and Spark, used recently and regularly
Real experience with cloud data platforms (Databricks strongly preferred; Snowflake, Synapse, or similar accepted) on AWS, Azure, or GCP
Demonstrated ability to lead a mixed team of employees and contractors: setting expectations, managing performance, building cohesion across employment types
Fluency with modern engineering practices: Git, CI/CD, automated testing, infrastructure-as-code, DataOps
The instinct to understand why something is being built, not just how.
Intellectual curiosity about the business domain you're working in
Clear communication skills; you can explain a technical tradeoff to a business leader and a business requirement to an engineer with equal ease

Nice To Haves

Experience with Databricks specifically: Unity Catalog, Delta Lake, medallion architecture, Databricks workflows
Experience with dbt or similar transformation frameworks
Familiarity with data governance patterns: lineage, access controls, metadata management, data quality frameworks
Prior work in financial services, insurance, benefits, or consulting environments
Experience with document or unstructured data ingestion pipelines
Exposure to LLM-based tooling, AI-assisted development, or analytics engineering

Responsibilities

Lead a delivery squad of 4-8 data engineers (employees and contractors) assembled against a business outcome.
Set the technical direction, decompose work, manage sprint-level execution, and are accountable for what the squad ships.
Write code, build pipelines, and debug production issues.
Design solutions in terms of data models, medallion architectures, ingestion contracts, and reusable patterns.
Ensure solutions are maintainable and understandable.
Work directly with Engagement Leads and business stakeholders to understand needs and define 'done'.
Translate business problems into data solutions and push back when requests don't make technical sense.
Explain complexity to non-technical leaders without jargon.
Drive engineering standards including CI/CD, version control, testing, code review, and documentation.
Raise the bar for engineering practices within the squad.
Focus on developer experience and operational excellence.
Operate on a modern stack including Databricks (Unity Catalog, Delta Lake, Spark, medallion architecture) running on AWS and Azure.
Work with infrastructure-as-code, Git-based workflows, and pipeline orchestration tooling.