IT Solution database engineer

Key Responsibilities Data Integration & ETL Development Design, develop, test, and maintain SQL Server Integration Services (SSIS) packages for data extraction, transformation, and loading (ETL). Integrate data from multiple internal and external sources, including SQL Server databases, flat files, APIs, cloud platforms, and third-party applications. Develop robust error handling, logging, and monitoring mechanisms within ETL processes. Troubleshoot and resolve ETL failures, performance bottlenecks, and data quality issues. Data Warehouse Development Design and maintain enterprise data warehouses, data marts, and staging environments. Develop dimensional models including star and snowflake schemas. Implement data cleansing, transformation, and standardization processes. Collaborate with business stakeholders to translate reporting and analytics requirements into scalable warehouse solutions. SQL Development & Performance Optimization Write complex, highly optimized T-SQL queries, views, functions, and stored procedures. Develop efficient data retrieval and transformation logic across large datasets. Analyze execution plans and optimize database performance through indexing, partitioning, and query tuning. Ensure scalable and maintainable database solutions that support growing business needs. Data Quality & Governance Implement data validation processes to ensure accuracy, completeness, and consistency. Identify and resolve data discrepancies across systems. Support data governance initiatives and maintain metadata documentation. Ensure compliance with organizational security and data management standards. Reporting & Analytics Support Support reporting teams by developing data structures optimized for BI tools such as Power BI, SSRS, or Tableau. Create and maintain reusable datasets and reporting views. Assist analysts and business users with complex data requests and ad-hoc analyses. Documentation & Collaboration Create and maintain technical documentation for ETL processes, data mappings, warehouse structures, and database objects. Participate in architecture and design reviews. Collaborate with developers, DBAs, business analysts, and project managers throughout the SDLC. Support production deployments and post-implementation troubleshooting.   Required Qualifications Education Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Engineering, or a related discipline. Experience 5+ years of hands-on experience in Data Warehouse Development. 5+ years of SQL Server development experience. 3+ years of experience developing and supporting SSIS packages and ETL solutions. Experience working with large enterprise databases and high-volume transactional systems. Required Technical Skills Database Technologies Microsoft SQL Server 2016/2019/2022 SQL Server Integration Services (SSIS) SQL Server Reporting Services (SSRS) SQL Server Agent SQL Development Advanced T-SQL programming Stored Procedures   Views   Functions   Common Table Expressions (CTEs)   Window Functions   Query Optimization   Execution Plan Analysis   Indexing Strategies   Data Warehouse Concepts   ETL/ELT Methodologies   Data Modeling   Star Schema   Snowflake Schema   Slowly Changing Dimensions (SCD)   Fact and Dimension Tables   Data Governance   Master Data Management   Tools & Methodologies   Azure DevOps or Git   Agile/Scrum Development   Data Validation & Reconciliation   Root Cause Analysis   Preferred Qualifications   Experience with Azure Data Factory (ADF).   Experience with Azure SQL Database or Synapse Analytics.   Experience supporting Power BI semantic models and datasets.   Knowledge of data lake and modern analytics architectures.   Microsoft DP-203, DP-300, or related certifications.   Key Competencies   Strong analytical and problem-solving skills.   Exceptional attention to detail and data accuracy.   Ability to work independently and manage multiple priorities.   Strong verbal and written communication skills.   Customer-focused approach to delivering business solutions.   Continuous improvement mindset focused on performance and scalability.   Success Measures     The Data Warehouse Developer will be evaluated based on:     ETL reliability and successful batch execution rates.   Data quality and accuracy.   Query and report performance improvements.   Timely delivery of integration and reporting solutions.   Documentation quality and adherence to development standards.   Reduction of manual data processing through automation.     This version is aligned with an enterprise SQL Server/Data Warehouse environment such as Eurofins' SSIS/SSRS-driven reporting and analytics platforms. Eurofins Scientific is an international life sciences company, providing a unique range of analytical testing services to clients across multiple industries, to make life and our environment safer, healthier and more sustainable. From the food you eat, to the water you drink, to the medicines you rely on, Eurofins laboratories work with the biggest companies in the world to ensure the products they supply are safe, their ingredients are authentic and labelling is accurate. The Eurofins network of companies believes that it is a global leader in food, environment, pharmaceutical and cosmetic product testing and in discovery pharmacology, forensics, advanced material sciences and AgroScience contract research services. It is also one of the market leaders in certain testing and laboratory services for genomics, and in the support of clinical studies, as well as in biopharma contract development and manufacturing. It also has a rapidly developing presence in highly specialised and molecular clinical diagnostic testing and in-vitro diagnostic products. In over 37 year