Data Engineer

Ework Group, founded in 2000 and listed on Nasdaq Stockholm, has around 13,000 independent professionals on assignment. The company provides total talent solutions partnering with clients in private and public sectors, focusing on IT/OT, R&D, Engineering, and Business Development to deliver sustainable value through holistic talent management.

• Strong end-to-end experience in analytics platforms, data products, data warehouses (Star schema, Data Vault, multidimensional, tabular), and modern architectures.
• Expert in SQL/T-SQL, Python, Apache Spark, Databricks, Delta Lake, Azure Data Factory; batch/incremental/CDC/event-driven patterns.
• Data modeling (logical/physical), ETL/ELT design (high-performing SSIS packages, script components in C#), API development/maintenance.
• Cloud-native (Azure platforms), legacy modernization (SSIS to cloud), technology trade-offs for storage/processing.
• Proactive self-starter with analytical/problem-solving skills, task management, and ambition to grow into Data/Analytics Architect.
• Agile methodology, JQL/Confluence experience; clear documentation and business communication in English.

Nice to have:

• Master data management tools/practices, Power BI (semantic models, DAX, front-ends), SSRS, MDX.
• Team Foundation Server versioning, dispatching systems.

• Co-drive solution design with Business Analysts, defining target architectures, data models, flows, and integration patterns aligned with UDP principles (cloud-native, scalable, secure).
• Handle data ingestion, cleansing, standardization, transformation, and API provisioning from source systems (e.g., master data customer/product).
• Optimize existing ETL/ELT flows, build infrastructure for extraction/loading from diverse sources, and modernize legacy solutions.
• Assess feasibility, risks, dependencies; create implementation-ready designs, documentation, diagrams, and CI/CD automation.
• Collaborate with stakeholders, data stewards, architects, and teams to implement non-functional requirements (quality, security, stability) and support data-driven services.
• Evaluate/improve analytics solutions, integrate systems, and communicate technical topics to business audiences.