Fabric Data Engineer (All genders)

Description

You will join an international team of 2,500 specialists who combine software, data, AI and human expertise to build digital products, services and operating models with measurable business results.

The team builds and runs intelligence across the whole value chain, with a focus on people, real human contact and a supportive, inclusive environment.

Responsibilities

• Build, run and grow batch and near-real-time data pipelines in Microsoft Fabric using Data Factory pipelines, Dataflow Gen2, notebooks and Spark job definitions.
• Set up and maintain Lakehouse and Warehouse solutions in OneLake using medallion, dimensional and data-product patterns.
• Write ingestion, cleansing, transformation and integration logic in Python, PySpark, Spark SQL, T-SQL and, where suitable, Power Query.
• Bring together structured, semi-structured and unstructured data from cloud, on-premises, SaaS, API, file and streaming sources.
• Tune pipelines and analytical workloads for speed, reliability, maintainability and efficient use of Fabric capacity.
• Apply engineering standards covering data quality, observability, metadata, lineage, security, testing, error handling and production support.
• Partner with data scientists, BI developers, analysts, architects and business stakeholders to turn data needs into reusable, analytics-ready solutions.
• Support CI/CD, source control, automated deployment, environment management and release practices for Fabric workspaces and data products.
• Assess new Microsoft Fabric capabilities and propose practical improvements to the platform and delivery approach.
• Share your knowledge and keep technical documentation, runbooks, standards and best practices current.

Requirements

• 5+ years of hands-on data engineering experience, including designing and delivering large-scale pipelines and cloud data platforms.
• Solid hands-on work with Microsoft Fabric, covering Lakehouse, OneLake, Data Factory pipelines, notebooks, Apache Spark and Fabric Warehouse.
• Advanced Python and SQL skills, with hands-on PySpark or Spark SQL for distributed data processing.
• Strong grounding in data integration, ETL/ELT, data modeling, data architecture and analytics-focused solution design.
• Proven experience building dependable batch processing and integrating data from several enterprise source systems.
• Working knowledge of Delta Lake, including partitioning, schema evolution, incremental loading and performance optimization.
• Experience applying security, access control, data-quality checks, monitoring, logging, testing and production support to data solutions.
• Experience with Git-based development and CI/CD using Azure DevOps, GitHub Actions or similar tools.
• Ability to explain technical decisions clearly, work well across functions and own work from design through to production.
• Experience with further Fabric capabilities such as Dataflow Gen2, Eventstream, Real-Time Intelligence, Direct Lake, semantic models or Power BI.
• Knowledge of Microsoft Purview, Microsoft Entra ID, workspace governance, sensitivity labels, lineage and enterprise data governance.
• Experience with Azure services that often pair with Fabric, such as Azure Data Lake Storage, Azure SQL, Azure Functions, Event Hubs, Key Vault or private networking.
• Exposure to infrastructure as code and deployment automation with Terraform, Bicep, REST APIs or Fabric deployment pipelines.
• Knowledge of streaming technologies such as Kafka or Azure Event Hubs.
• Experience moving solutions from Azure Data Factory, Azure Synapse Analytics, Databricks or other cloud data platforms to Microsoft Fabric.
• Relevant Microsoft certifications, such as Fabric Data Engineer Associate, or equivalent hands-on expertise.
• Experience in Agile delivery and in consulting or customer-facing projects.

Conditions

Hybrid working model with a high degree of flexibility.

Every application is treated equally, and any discrimination or harassment based on gender, age, skin color, religion, sexual orientation, origin, disability, gender identity or other protected characteristics is opposed.

Benefits

• Training programs, free language courses, competence centers and an active tech community for professional and personal growth.
• Workation, flexible hours, parental support and sabbaticals.
• Sustainability Hub, diverse communities, a Diversity Taskforce and after-work activities.
• Public transport tickets and job bikes.
• Employee conditions on leasing or buying a vehicle through Volkswagen, health offers, supplementary insurance, a pension plan and various discounts.