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Director, Enterprise Data Engineering & Analytics

Marsh McLennan Inc.

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At a glance

Compensation
No compensation found
Location
NEW YORK, NY
Work Authorization
Not specified

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Job overview

Oliver Wyman Technology seeks a Director to lead and scale enterprise data engineering and analytics capabilities. The role combines strategic leadership with hands-on technical expertise to build trusted, governed, scalable data foundations for analytics, reporting, and AI. The Director will lead multidisciplinary teams, deliver modern cloud data platforms and analytics products, and partner with business, technology, and AI leaders to support machine learning and generative AI adoption.

Skills & qualifications

RequiredNice to have

Skills

DatabricksAWSCloud Data PlatformsPythonSQLSparkData ModelingETL/ELTCI/CDObservabilityGovernance ToolingAI-Ready Data ArchitectureMachine LearningGenerative AISecurityPrivacyRegulatory RequirementsConsulting DeliveryClient-Facing DeliveryStreaming PlatformsReal-Time ArchitecturesKafkaPub/SubKinesisVector-Enabled Data PlatformsRetrieval-Optimized Data ModelsGenerative AI Data PatternsAzureGCPHybrid Cloud

Qualifications

10+ Years Data Platform Experience5+ Years Engineering Team LeadershipDatabricks CertificationAWS Solutions Architect/Specialty Certification

Full job description

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. We will count on you to: 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. What you need to have: 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. What makes you stand out: 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. Why join our team: We help you be your best through professional development opportunities, interesting work and supportive leaders. We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities. Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being. 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 embracing a diverse, inclusive and flexible work environment. We a m to

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