Head of Data Engineering

Brightwater Executive

Dublin

On-site

EUR 140,000 - 210,000

Full time

21 hours ago
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Job summary

Brightwater Executive in Dublin city centre is seeking a Head of Data Engineering to own the firm's data platform strategy and production-grade delivery in AWS. This hands-on leadership role combines strategic direction with execution across ingestion, transformation, and data governance.

You will lead a cross-functional team, define standards, mentor engineers, and build scalable pipelines that enable AI, analytics, and regulatory reporting in a fast-growing financial services environment.

Qualifications

  • Senior engineering or technology leadership experience in cloud-first environments.
  • Proven track record delivering production ETL/ELT pipelines in AWS.
  • Experience designing data platform architecture, technical standards and reusable engineering patterns.
  • Strong technical judgement and ability to influence direction.
  • Degree in CS/Engineering/Math/Physics or related field.

Responsibilities

  • Define the technical data engineering strategy across ingestion, transformation, modelling, quality, lineage and consumption.
  • Establish reusable patterns for third-party extracts, vendor data, APIs, bordereaux, underwriting data, exposure data, claims data and internal analytics.
  • 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.

Skills

Python
SQL
AWS (Data Platform)
ETL/ELT pipelines
Data modelling
APIs
Git / GitHub
CI/CD
Infrastructure as Code
Data quality & governance
Iceberg/Delta Lake
Regulated industry experience
GenAI / AI platforms

Education

BSc/MSc in Computer Science, Engineering, Mathematics, Physics or related discipline

Tools

S3
Glue
Lambda
ECS
DynamoDB
Redshift

Job description

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.
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