Full-Time

Director Enterprise Data Engineering & Analytics

Updated on 8/22/2026

Marsh & McLennan

Marsh & McLennan

Risk, insurance and business consulting

Compensation Overview

$139k - $277.9k/yr

+ Performance-based incentives

Company Does Not Provide H1B Sponsorship

New York, NY, USA

Hybrid

At least three days per week in the local office or onsite with clients.

Bachelor's

Category
Data & Analytics (2)
,
Required Skills
LLM
Microsoft Azure
Python
Apache Spark
SQL
Machine Learning
Apache Kafka
Kinesis
ETL
AWS
Observability
Data Modeling
Data Governance
DevOps
Databricks
Data Analysis
Google Cloud Platform
Requirements
  • A degree in Computer Science, Engineering, Data Science, Statistics, or equivalent practical experience is required.
  • At least 10 years of experience designing and delivering data platforms or large-scale data systems, including at least 5 years leading and scaling high-performing engineering teams.
  • Proven experience delivering enterprise cloud data platform transformations, with strong hands-on expertise in Databricks and Amazon Web Services.
  • Strong software and data engineering skills, including Python and SQL, plus experience with Apache Spark, data modeling, extract-transform-load/extract-load-transform, continuous integration and continuous delivery, observability, and governance tooling.
  • Experience designing artificial-intelligence-ready data architectures that support machine learning and generative artificial intelligence use cases, with strong knowledge of security, privacy, and regulatory requirements.
Responsibilities
  • Define and evolve the enterprise data strategy and roadmap, aligning investments with business priorities and future artificial intelligence capabilities.
  • Lead, hire, and mentor globally distributed data engineering, analytics engineering, and data science teams while fostering a high-performing, inclusive culture.
  • Drive the design and delivery of trusted, reusable data products that power analytics, reporting, machine learning, and generative artificial intelligence across the firm.
  • Provide hands-on technical leadership by reviewing architecture, optimizing key components, resolving production issues, and setting engineering standards and delivery practices.
  • Partner with senior business, consulting, technology, and artificial intelligence platform leaders to shape the data roadmap, influence investment decisions, and manage vendor and platform priorities.
Desired Qualifications
  • Consulting or client-facing delivery experience in a complex enterprise environment.
  • Experience with streaming platforms and real-time architectures such as Kafka, Pub/Sub, or Kinesis.
  • Familiarity with vector-enabled data platforms, retrieval-optimized data models, and other modern generative artificial intelligence data patterns.
  • Exposure to additional cloud platforms such as Azure or Google Cloud Platform, or hybrid cloud environments.
  • Professional certifications such as Databricks or Amazon Web Services Solutions Architect/Specialty.

Marsh, formerly Marsh McLennan, is a global professional services firm focused on risk, insurance, reinsurance, talent and business strategy. Its operating businesses help organizations arrange coverage, model and transfer risk, design workforce programs and address complex management questions. Clients range from growing companies to governments and multinational enterprises. The group combines advisory expertise with insurance-market access and data, making it broader than an insurance broker alone while remaining primarily a business-to-business services organization.

Company Size

N/A

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

N/A