Head of Data Engineering

This is a unique opportunity to join a fast-growing financial service’s tech and innovation hub scale up, here in Dublin city centre.

This is a hands-on leadership role suited to someone who can operate at both strategic and execution levels, with company-wide technical ownership of for the firms data engineering strategy with responsibility for translating that strategy into production-grade platform delivery.

As Head of Data Engineering, you will be accountable for how the company engineers its long-term data asset platform which is being built in AWS using modern data engineering practices and cloud-native infrastructure

This will suit someone who can think creatively and develop innovative, technology and data-driven solutions that create differentiation in the insurance market. They will be supported by a culture of ambition, innovation and drive.

Key Responsibilities:

Technical Data Engineering Strategy

• Define the technical data engineering strategy across ingestion, transformation, modelling, quality, lineage, metadata and consumption
• Establish reusable engineering patterns for third-party platform extracts, vendor data, APIs, bordereaux, underwriting data, exposure data, claims data and internal analytical outputs
• Define the technical roadmap for the data platform and sequence engineering investment
• Set architectural principles and standards for how the data asset is engineered, maintained, controlled and consumed
• Translate platform architecture and requirements into robust, scalable implementations
• Design and implement data ingestion and transformation pipelines combining fragmented datasets including exposure data, modelling outputs, internal analytics and unstructured information
• Build shared libraries to ensure consistent data access across applications
• Build datasets and platform capabilities supporting AI and modelling workflows across the business
• Define schemas and storage structures across different layers of the platform

Data Quality & Technical Governance

• Define and implement technical standards for data quality, validation, testing, monitoring, lineage and observability
• Design and implement catalogue, metadata and lineage capabilities that make core datasets discoverable, auditable and reusable
• Partner with data governance stakeholders to translate agreed business definitions and calculation logic into version-controlled data models and transformations
• Ensure pipelines meet requirements around auditability, consistency and reproducibility

Cross-Functional Technical Leadership

• Collaborate with Capital & Risk, Underwriting, Finance & Operations, Platform Engineering and future data governance functions
• Act as the senior technical authority for data engineering decisions across theplatform and data asset
• Provide technical guidance and mentorship to engineers and analysts working with data
• Help shape the future data engineering capability, including engineering standards, delivery patterns, hiring priorities and team design

The Ideal Candidate and Attributes:

• Proven experience in a senior engineering, or technology leadership role with strong experience defining and leading data engineering strategy in a cloud-first environment.
• Experience working across ingestion, transformation, storage and consumption layers, with a track record leading / building production ETL/ELT pipelines in AWS
• Experience designing data platform architecture, technical standards and reusable engineering patterns
• Strong technical judgement, with the ability to influence architecture and engineering direction
• BSc/MSc in Computer Science, Engineering, Mathematics, Physics or a related discipline, or equivalent practical experience

Technical Skills:

• Programming: Python; SQL
• AWS Data Platform - S3; Glue; Lambda; ECS; DynamoDB
• Redshift or similar analytical databases
• Data Engineering - ETL / ELT pipeline design; Data modelling and schema design
• Working with APIs and external data providers
• Data validation and monitoring
• Software Engineering - Git / GitHub; CI/CD pipelines; Infrastructure-as-code
• Strong understanding of modern software engineering and cloud infrastructure concepts
• Experience with open table formats (Iceberg, Delta Lake or similar) would be advantageous.
• Experience in a greenfield environment.
• Experience in financial services,insurance, or another regulated industry.
• Exposure to data,AI, or GenAI-enabled platforms.
• Familiarity with modern enterprise integration across application, data, and cloud domains.