Director - Data Engineering

Job title -Director, Data Engineering & Analytics

Overview Oliver Wyman Technology is seeking an experienced, handson Director of Data Engineering & Analytics to lead and scale our enterprise data platform and analytics capability. This role combines strategic ownership with technical leadership: you will grow and mentor a multidisciplinary team (data engineers, analytics engineers and data scientists) and deliver productiongrade data platforms, analytics products and AI/ML solutions that generate measurable business value for the firm and our clients. The ideal candidate has deep, practical experience with Databricks and AWS and a proven track record of productionising data and ML systems at scale.

Responsibilities

• Lead, hire and mentor a highperforming team; set priorities, delivery cadence and engineering standards to scale the capability.
• Own the roadmap and delivery of enterprise data platforms and analytics products, including data lakes/warehouses, ETL/ELT, streaming and data APIs.
• Provide handson technical leadership: design and review architecture, implement or optimise key components, and resolve production incidents as required.
• Drive adoption of Databricks best practice (Spark optimisation, Delta Lake, Unity Catalog) and core cloud platform patterns.
• Productionise AI/ML: guide feature engineering, model deployment, monitoring, versioning, explainability and MLOps workflows.
• Establish and enforce CI/CD, automated testing, observability and incident response for data pipelines, models and analytics services.
• Define and enforce data governance, security, privacy and compliance standards in partnership with legal and security teams.
• Partner with business leaders, product managers and consulting teams to translate business problems into scalable data and AI solutions; manage stakeholder expectations and prioritisation.
• Manage vendor relationships and platform budgets; evaluate and procure thirdparty tools where appropriate.
• Foster a culture of data literacy, experimentation, inclusivity and continuous improvement.

Must have skills and qualifications

• Degree in Computer Science, Engineering, Data Science, Statistics or equivalent practical experience.
• 10+ years designing and delivering data platforms or largescale data systems; 5+ years managing engineering teams and senior technical leaders.
• Proven experience delivering endtoend cloud data platform transformations at enterprise scale.
• Handson Databricks experience (Spark optimisation, Delta Lake, workspace/job orchestration, Unity Catalog) at scale.
• Strong practical experience building and operating data solutions on AWS (e.g., S3, Glue, Redshift/Athena, Lambda, EKS/ECS; infrastructure as code such as CloudFormation or Terraform).
• Solid understanding of AI/ML production patterns, including model development, deployment, monitoring, drift detection and MLOps.
• Strong software and data engineering skills: Python and SQL required; Scala/Java advantageous. Experience with Spark, data modelling, ETL/ELT and streaming fundamentals.
• Experience implementing CI/CD, container orchestration and observability for data systems.
• Knowledge of data governance, metadata/catalogue tools, lineage and data quality frameworks (i.e. Great Expectations or equivalent).
• Strong grasp of security, data privacy and regulatory requirements (e.g., GDPR, data residency).
• Professional certification such as Databricks or AWS (Solutions Architect / Specialty).

Nice to have

• Consulting or clientfacing delivery experience.
• Experience with streaming platforms (Kafka, Pub/Sub, Kinesis) and realtime architectures.
• Familiarity with generative AI, LLMs and conversational AI production patterns.
• Exposure to other cloud providers (Azure/GCP) or hybrid cloud architectures.