Managing Director, Data Products & Engineering

The Managing Director, Data Products & Engineering leads the development, expansion, and delivery of Plymouth Rock’s enterprise data assets across our data warehouse and data lake environments.

 

This role is responsible for ensuring that enterprise data is complete, high fidelity, low latency and continuously expanding to meet the needs of Business Intelligence, Machine Learning, and AI data services and consumption patterns. You will partner closely with the heads of Date Governance and Data Services to ensure that Plymouth Rock’s data distribution and consumption is well organized, well governed and accessible at speed and scale.

 

This leader will organize and execute work through agile data products aligned to business and enterprise data domains consistent with a growing insurance organization. The role is responsible for ensuring each data product squad meets clear objectives on a rapid development cycle serving the organization’s AI ambitions.

 

Key Responsibilities

1. Enterprise Data Product Strategy & Delivery

• Lead the development of enterprise data products aligned to business and enterprise domains, ensuring data is structured, accessible, and reusable across the organization.
• Define and prioritize the data development roadmap in alignment with business needs, AI/ML use cases, and platform evolution.
• Ensure data products are delivered incrementally through agile development cycles, with clear ownership, accountability, and measurable outcomes.
• Drive the transition from project-based delivery to a product-based operating model, while maintaining the ability to support enterprise project demands through scaled agile execution.

1. Continuous, Rapid Data Expansion (Depth & Breadth)

• Own the continuous expansion of enterprise data across data products leveraging both internal and external sources.
• Ensure that all relevant enterprise data—structured, unstructured, and streaming—is ingested, harmonized, and made available for consumption.
• Partner with the Third-Party Data capability to integrate external data into enterprise data products and ensure broad accessibility across use cases.
• Partner with application developers to identify and eliminate data leakage by systematically capturing all data generated at the frontline operation, including previously unmanaged or unstructured sources.

1. Data Engineering & Platform Execution

• Lead teams of data engineers and product owners responsible for ingestion, transformation, and delivery of data across the enterprise data warehouse and data lake.
• Ensure efficient and scalable data pipelines that support both deterministic (reporting) and probabilistic (AI/ML) consumption patterns.
• Continuously improve data ingestion speed, pipeline reliability, and processing efficiency to meet evolving business and AI demands.
• Embed business context into data product development, ensuring outputs are actionable and aligned to operational needs.
• Partner with Data Governance & Architecture to ensure data products align with classification, lineage, and access standards. Ensure consistent, well organized documentation.

1. Agile Product Execution & Scaled Delivery

• Align and organize data platform into an agile product structure operating mutually exclusive, collectively exhaustive. Ensure maximum throughput and minimum handoffs and bottlenecks.
• Ensure products squads are empowered to deliver incrementally, operate autonomously, and are accountable for measurable outcomes aligned to the objectives of the data office.
• Establish and manage agile delivery practices, including sprint cycles, backlog prioritization, and release management.
• Coordinate with adjacent teams (Applications, Data Services, and AI/ML engineering) through a scaled agile framework, ensuring alignment across interdependent workstreams.

Qualifications

 

Education

• Bachelor’s degree in Data Science, Computer Science, Engineering, Actuarial Science, Business Administration, or a related field required.
• Master’s degree (MS in Data Analytics, Artificial Intelligence, or Information Management) preferred.

Experience Preferred