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.