Data Engineer

Background

CK Hutchison Holdings Limited (CK Hutchison) is a multinational conglomerate committed to innovation and technology, with operations in over 50 markets and employing over 300,000 employees worldwide. Its portfolio spans four core sectors: ports and related services, retail, infrastructure, and telecommunications. In Europe, CK Hutchison has investments in 23 countries, and currently employs over 125,000 employees.

CKDelta is CK Hutchison’s data innovation company. Our mission is to deliver long-term sustainable value through innovative applications that leverage data assets from across the CKHH Group. To do this, we combine a wide variety of datasets from the group companies to create new products to be used internally and externally.

About the Role

We are looking for a Data Engineer with 3-6 years of hands-on experience to design, build and maintain reliable data pipelines across modern cloud data platforms.

The successful candidate will work with senior data engineers, data architects and analysts to deliver scalable data solutions that enable reporting, analytics and business decision-making.

This role is ideal for someone who has progressed beyond junior-level delivery, can independently contribute to production data pipelines, and is continuing to develop their expertise in architecture, optimisation and platform design.

Key Responsibilities

Pipeline Development & ETL

• Design, build and maintain ETL/ELT data pipelines using Python, SQL and cloud-based tooling
• Write SQL queries to extract, transform and validate data from relational databases and cloud storage
• Develop Python scripts for data ingestion, transformation and automation tasks
• Support ingestion of data from multiple sources - databases, REST APIs, flat files (CSV, JSON, Parquet)
• Implement error handling, logging and retry logic to improve pipeline reliability and operational support
• Apply Medallion (Bronze / Silver / Gold) architecture patterns in real delivery scenarios

Cloud & Platform

• Develop data processing workloads in Azure Databricks, including notebooks, jobs and workflows
• Support data pipeline orchestration using Azure Data Factory, including triggers, Linked Services and pipeline scheduling
• Store and access data in Azure Data Lake Storage Gen2 (ADLS Gen2) and Delta Lake format
• Apply Unity Catalog principles for data access, permissions and governance
• Work with relevant Azure services such as Key Vault, Azure SQL, Blob Storage and Event Hubs where required by the solution

Data Quality & Documentation

• Create and run data validation checks including row counts, null checks, referential integrity and reconciliation
• Investigate, troubleshoot and resolve data pipeline failures and data quality issues
• Document data pipelines, transformation logic, data dictionaries and process notes for team use
• Contribute to testing and deployment activities including unit testing, integration testing and production release support

Collaboration & Delivery

• Collaborate with senior engineers, data architects and analysts to refine requirements and deliver technical solutions
• Translate business data needs into clear technical specifications and implementation tasks
• Use Git for source control - branching, committing, pull requests within an established team workflow
• Participate in Agile ceremonies - stand-ups, sprint planning, backlog refinement
• Share knowledge with the team and continue building expertise in cloud data engineering, Databricks and modern data platform practices
• Develop and maintain dashboards and basic reports in Power BI to support analytical consumers

Required Skills & Experience

Essential

• 3-6 years' experience in Data Engineering, ETL/ELT development, Analytics Engineering, or Cloud Data Platforms
• Strong SQL skills, including complex joins, CTEs, window functions, optimisation, and troubleshooting
• Proficiency in Python for data processing, automation, and pipeline development
• Experience building and supporting ETL/ELT pipelines in production environments
• Working knowledge of cloud platforms, ideally Microsoft Azure
• Experience using Git and collaborative development practices
• Understanding of relational databases, data modelling, and dimensional modelling concepts
• Strong analytical, problem-solving, and communication skills
• Right to work in Ireland is mandatory

Good to Have

• Azure Databricks and PySpark
• Delta Lake and Lakehouse architectures
• Azure Data Factory or similar orchestration tools
• Power BI reporting and basic DAX
• dbt or other modern data transformation frameworks
• Experience with data governance and access management practices

Qualifications

• Bachelor’s degree in computer science, Data Science, Mathematics, Engineering or a related STEM field is preferred. Equivalent practical experience will be considered where candidates can demonstrate sustained hands-on delivery of data engineering work.
• Databricks Certified Data Engineer Associate, Microsoft AZ-900 Azure Fundamentals or DP-700 Fabric Data Engineer Associate certification are desirable
• GitHub repositories, project portfolios, or examples of delivered solutions are welcomed

What We Offer

• Competitive salary and bonus opportunities
• Hybrid working model, based out of our office on Sir John Rogerson's Quay, Dublin
• 25 days annual leave
• Pension, health insurance and other benefits
• Professional development and certification support
• Collaboration on innovative, cross-functional projects with global stakeholders
• Career progression within a growing data and technology team