Director, Enterprise Data Engineering & Analytics

Marsh McLennan•New York, NY

2d•$139,000 - $277,900•Hybrid

About The Position

Oliver Wyman Technology is seeking an experienced Director of Enterprise Data Engineering & Analytics to lead and scale our enterprise data platform and analytics capabilities. This strategic leadership role is responsible for building trusted, governed and scalable data foundations that power analytics, reporting and AI across the firm. Working closely with AI platform, application and business teams, the Director will ensure enterprise data is discoverable, high quality and AI-ready, enabling the successful adoption of machine learning and generative AI capabilities. The role combines strategic leadership with hands-on technical expertise, leading multidisciplinary teams while delivering modern cloud data platforms and analytics products that create measurable business value. The ideal candidate has deep, practical experience with Databricks and AWS and a proven track record of delivering enterprise data platforms that enable analytics, machine learning and generative AI at scale.

Requirements

Degree in Computer Science, Engineering, Data Science, Statistics, or equivalent practical experience.
10+ years designing and delivering data platforms or large-scale data systems, including 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 AWS.
Strong software and data engineering skills, including Python and SQL, plus experience with Spark, data modeling, ETL/ELT, CI/CD, observability, and governance tooling.
Experience designing AI-ready data architectures that support machine learning and generative AI use cases, with strong knowledge of security, privacy, and regulatory requirements.

Nice To Haves

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 AI data patterns.
Exposure to additional cloud platforms such as Azure or GCP, or hybrid cloud environments.
Professional certifications such as Databricks or AWS Solutions Architect/Specialty.

Responsibilities

Define and evolve the enterprise data strategy and roadmap, aligning investments with business priorities and future AI 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 AI 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 AI platform leaders to shape the data roadmap, influence investment decisions, and manage vendor and platform priorities.