Technical Lead Data

The key distinction: This is not a people-management role that happens to involve data. It's a hands-on technical leadership role where managing people is one of the things you do, alongside designing architectures, 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.

What You Will Do:

• Lead a delivery squad. You'll run a pod of 4-8 data engineers (employees and contractors) assembled against a business outcome. You set the technical direction, decompose work, manage sprint-level execution, and are accountable for what the squad ships. When the initiative concludes or transitions to steady state, you and your engineers move to the next priority.

• Build with your hands. You write code. You build pipelines. You debug production issues. You're comfortable in SQL, Python, and Spark, and you use them regularly, not as a party trick, but as your primary tools. When something is broken or behind, you can step in and do the work, not just escalate it.

• Design before you build. You think in terms of data models, medallion architectures, ingestion contracts, and reusable patterns. You design solutions that are maintainable and that the next engineer can understand without an archaeology expedition. You care about schema evolution, data quality checks, idempotency, and lineage, not because someone told you to, but because you've been burned when those things were missing.

• Engage with the business. You're not building pipelines into a void. You'll work directly with Engagement Leads and business stakeholders to understand what they need, why they need it, and what "done" looks like. You translate business problems into data solutions and push back when what's being asked for doesn't make technical sense. You're comfortable in a room with non-technical leaders and can explain complexity without hiding behind jargon.

• Drive engineering standards. CI/CD, version control, testing, code review, documentation: these aren't aspirational for you, they're how you've always worked. You'll bring these practices to your squad and raise the bar for everyone around you. You care about developer experience and operational excellence, not just feature delivery.

• Operate on a modern stack. The platform is Databricks (Unity Catalog, Delta Lake, Spark, medallion architecture) running on AWS and Azure. You'll work with infrastructure-as-code, Git-based workflows, and pipeline orchestration tooling. If you've spent the last several years in the Databricks ecosystem, great. If you've built equivalent capabilities on other modern platforms and can ramp quickly, that works too.

What We're Looking For:

Essential:

• 5+ years of hands-on data engineering experience, with at least some time leading or mentoring other engineers

• Strong proficiency in SQL, Python, and Spark, used recently and regularly, not years ago

• 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

Valued:

• 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

Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X.

Marsh is committed to creating a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.