Data Engineer

Join an innovative data team in a global financial organization and help build a large-scale data platform on Azure and Databricks!

• 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.

Nice to have:

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

• Design, develop, and maintain data structures and databases in MS SQL Server and Data Lake (Pond DB).
• 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.