Microsoft Fabric Data Engineer

In this role you will design and deliver enterprise-grade data and analytics solutions using Microsoft Fabric and Power BI. You will collaborate with solution architects, client IT and data teams to translate architectures into production-ready pipelines, ensuring quality and maintainability. You’ll work on data integration, governance, and real-time analytics to unlock trusted data for regulated industries. This is a hybrid, client-facing data engineering opportunity at scale within a global tech services environment.

• ESPP
• life assurance and income protection
• private medical and dental
• Employee Assistance Program
• pension plan
• CycleScheme/season ticket loans

• Implement end-to-end Microsoft Fabric solutions based on approved architecture (OneLake, Lakehouse, Warehouse, Data Factory pipelines, Dataflows Gen2, Notebooks, Real-Time Intelligence)
• Build medallion architectures (Bronze/Silver/Gold) with incremental loads and CDC
• Ingest data from diverse sources (SQL databases, APIs, files, SaaS, SAP, streaming) using pipelines and mirroring
• Write clean, tested PySpark, Spark SQL, T-SQL and KQL; optimize Delta tables
• Add data quality checks, validation rules, logging and alerting to pipelines
• Develop enterprise semantic models (star schema) using Direct Lake, Import or DirectQuery
• Write efficient DAX measures and Power Query (M) transformations
• Create reports and dashboards following design guidelines
• Implement row-level and object-level security and workspace permissions per security concept
• Tune model and report performance with tools like DAX Studio, Tabular Editor, BPA and Performance Analyzer

• 3+ years of hands-on data engineering, BI development or data platform implementation
• 1+ year of Microsoft Fabric experience with at least one production or PoC project
• 2+ years of Power BI development: semantic modeling, DAX, Power Query, Service administration and performance tuning
• Strong SQL (T-SQL) skills and working knowledge of Python/PySpark and Spark SQL in notebooks
• Hands-on experience with Azure data services (Azure Data Factory, ADLS Gen2, Azure SQL, Synapse or Databricks)
• Solid understanding of data warehousing and lakehouse concepts, Delta/Parquet and dimensional modeling (Kimball)
• Experience with Real-Time Intelligence (Eventstreams, Eventhouse/KQL, Activator)
• Ability to turn architecture documents into working, well-documented solutions
• Analytical mindset, structured working style and focus on quality
• English (B2+) and German (B1+) communication skills

• analytical mindset
• attention to quality
• cross-functional collaboration
• PySpark
• Spark SQL
• T-SQL