Technical Data Ecosystem Product Manager

Job Type:

Permanent

Build a brilliant future with Hiscox

Company description

Hiscox is a diversified international insurance group with a powerful brand, strong balance sheet and plenty of room to grow. Listed on the London Stock Exchange and headquartered in Bermuda (with the bulk of group leadership sitting in London), Hiscox has over 3,000 staff across 14 countries and 34 offices.

Structured by geography and product, Hiscox’s long-held business strategy has helped them grow from a niche Lloyd’s underwriter to an international insurance group with a powerful consumer brand.

Hiscox’s Purpose: “We give people and businesses the confidence to realise their ambitions”

The Role

Hiscox intends to operate a Data Mesh architecture for supporting Analytics and Integrations across the group. This will be known as “the data ecosystem”. The Ecosystem is being established in 2026 and this role will be a key part of its establishment as well as ongoing maintenance.

The Ecosystem Product Manager (Band 3b) is a key leadership role within the Global Data Function. Responsible for setting the product strategy and detailed roadmap for the Data Ecosystem, ensuring the Ecosystem is capable of meeting both present and future Analytics, AI and Integration needs.

The role is responsible for ensuring that the Ecosystem is kept evergreen, working with data engineering leads to adopt product changes from Vendors in the ecosystem. The role is also responsible for identifying where changes in the underlying technology may drive a need to change engineering standards.

Acting as the intersection between engineering teams, architecture and data this role ensures that the Ecosystem roadmap delivers tangible benefits, is aligned with stakeholder expectations, and adheres to industry best practices. This role is also responsible for matrix management of delivery teams and the ongoing coaching and mentoring of stakeholders in best practice environments, release management, deployment, estimating and testing.

The strategic data platform will be built on GCP. As Hiscox uses a federated model with platforms in Databricks and Snowflake, this role requires strong GCP experience and familiarity with Databricks and/or Snowflake.

Key Responsibilities

• Product Strategy & Vision: Define and communicate a clear vision for data ecosystem, setting strategic goals and roadmap that align with business objectives and market opportunities.
• Stakeholder Engagement: Collaborate with stakeholders (e.g. business, software engineering, architecture, data) to understand requirements, prioritise initiatives, and manage expectations.
• Strategic partnerships: Work with 3rd parties to generate fresh perspectives and also ensure successful delivery partnerships.
• Product Development Lifecycle Management: Lead cross-functional teams through ideation, design, development, testing, and deployment of data products, ensuring timely delivery and quality standards.
• Data Culture: Support the Data Engineering Chapter, ensuring technical blockers to good data culture are resolved within the roadmap
• Data Governance & Compliance: Ensure compliance with data privacy regulations (such as GDPR), data quality management practice are embedded in ecosystem design.
• Performance Monitoring & Optimisation: Track product performance using key metrics, conduct regular reviews, and implement enhancements based on data-driven insights.
• Communication & Documentation: Produce clear documentation, reports, and presentations for stakeholders, ensuring transparency and alignment throughout the product lifecycle.
• Backlog Management: Own, refine, and prioritize the data ecosystem product backlog (features, tasks, improvements) based on business value, technical needs, and stakeholder input as well as encouraging user adoption for new features.
• Cost Optimisation: Establish a value driven FinOps framework in collaboration with engineering (who build), finance (who budget) and business (who own the products)

Key Requirements / Person Specification

• Technical Proficiency:

  • Deep hands‑on expertise with GCP data and analytics services (BigQuery, Dataflow, Pub/Sub, IAM, monitoring), plus working knowledge of Databricks and/or Snowflake in federated enterprise environments.
  • Strong understanding of modern data architectures including Data Mesh, event-driven patterns, API‑based data products, and cloud‑native engineering standards.
  • Good working know…