Data Engineer - Hybrid

A financial and professional services business is seeking a Data Engineer to strengthen the data foundations behind its reporting, analytics and AI initiatives. Based in Belfast, you will build and maintain reliable data pipelines, bring together information from internal systems and make trusted data available for business decision-making.

Working with analysts and business stakeholders, you will develop ETL/ELT processes, support data warehouses and data lakes, and improve the quality and performance of the organisation’s data platform.

• Salary up to £60,000, depending on experience.
• Hybrid working with two days per week in the Belfast office.
• Company Benefits Pack
• Hands-on work with Microsoft Fabric, SQL Server and modern data integration tools.
• The opportunity to build pipelines that directly support new analytics, dashboard and AI use cases.
• Excellent career progression and skill up opportunities
• A collaborative environment with close interaction across data engineering, analytics and the wider business.
• First class modern company culture.

• Experience in data engineering or a closely related role, with the ability to deliver independently.
• Strong SQL and Microsoft SQL Server skills, including database development, troubleshooting and performance optimisation.
• Hands-on experience designing, building and maintaining ETL/ELT pipelines and integrating data from multiple sources.
• Experience with Microsoft Fabric or a comparable cloud data platform, alongside hands-on cloud experience.
• A solid understanding of data warehouses, data lakes and dimensional modelling, including star and snowflake schemas.
• Experience with relevant integration and reporting tools such as Fabric Pipelines, Azure Data Factory, SSIS, SSRS, Fivetran, Alteryx or dbt.
• A practical understanding of data quality, governance, access controls and secure data handling.
• Strong communication skills and the ability to translate business requirements into reliable technical solutions.
• A proactive approach to problem-solving, clear documentation and collaboration with technical and non-technical colleagues.

Python experience would be advantageous but is not essential. Experience migrating legacy systems and working with financial or commercial data would also be beneficial.