Data Engineer

For this role, we are looking for a balanced skill set, The on-premises side requires strong hands-on experience with SQL Server, T-SQL, SSIS and ETL/ELT development, while we also need solid experience with modern cloud-based data technologies. This hybrid requirement is important given our mix of on-premises and cloud solutions.

Requirements:

• 3+ years of professional experience in BI / Data Engineering, with strong experience in data warehousing and ETL/ELT.
• Expert-level SQL/T-SQL, including database object design, stored procedures, views, functions and query performance tuning.
• Hands-on experience with SQL Server, SSIS, SSRS and Power BI.
• Experience with Azure Data Factory and Azure data services, including designing, building, monitoring and troubleshooting data pipelines.
• Good understanding of Azure DevOps, Git/source control and CI/CD practices.
• Experience with Python for automation, data processing and reusable engineering components.
• Understanding of Microsoft Fabric, lakehouse concepts, Parquet-based storage and data snapshotting.
• Experience with API integrations is a plus; Workday integration experience would be an advantage.
• Experience working with finance and/or insurance data and understanding how data is sourced, integrated, governed and consumed across business systems, DWH and reporting solutions.
• Strong analytical, communication and problem-solving skills, with the ability to work effectively with business users, BI specialists and technical teams.

• English — B2 or higher.

   

Responsibilities:

• Design, develop and maintain DWH, Enterprise Data Platform and BI solutions using SQL Server, SSIS, Azure Data Factory and Microsoft BI technologies.
• Build and enhance ETL/ELT pipelines for data ingestion, transformation and orchestration, including API-based integrations where required.
• Develop and optimise SQL/T-SQL queries and database objects, including tables, views, stored procedures and functions.
• Develop and maintain Power BI reports, dashboards and semantic models in line with business and reporting requirements.
• Use Python for automation, data processing and reusable engineering solutions.
• Contribute to Microsoft Fabric/lakehouse development, Parquet-based storage and data snapshotting where required.
• Analyse data and investigate data quality, pipeline and reporting issues, implementing appropriate fixes and improvements.
• Work closely with business users and technical teams to analyse requirements, design solutions and deliver agreed development work.
• Apply engineering best practices, including testing, documentation, peer reviews, source control, monitoring and CI/CD deployments.

• Ensure solutions meet agreed technical, data governance, quality and release standards.

   

Our Benefits:

• Professional growth: Individual development plan, mentorship, reimbursement for professional certifications and English lessons, access to professional courses in Corporate Learning Management System.
• Community: Tech community and knowledge-sharing events, English speaking club, corporate library and book club, volunteering and charity initiatives.
• Wellbeing: Medical insurance, regular medical check-ups, sport reimbursement, paid vacation and sick leave, mental health support and events.
• Work environment: Fully-equipped offices, top-notch equipment, flexible work format, activities both in-office and online, Y-bucks and access to the Yalantis store.