Senior Data Platform Engineer – Microsoft Fabric

Graitec

Montcada i Reixac

On-site

EUR 40,000 - 60,000

Full time

5 days ago

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Job summary

Graitec is seeking a seasoned Data Platform Engineer to build and run the Microsoft Fabric data platform supporting Graitec’s reporting, analytics and AI initiatives. You will ingested data from Dynamics 365, CRM and telemetry, and design a layered data model enabling trusted analytics across the organization.

The role requires 6+ years in data engineering, strong SQL/PySpark skills, and hands-on Fabric experience.

Qualifications

6+ years of experience in Data Engineering, including at least two years working with Microsoft Fabric, Azure Synapse, or Databricks.
Strong experience with SQL and Python or PySpark, and data modelling for analytics.
Hands-on experience with Microsoft Fabric, including Lakehouse, Warehouse, Pipelines, Notebooks, and OneLake.
Experience integrating ERP and CRM data, ideally from Dynamics 365 Finance & Operations and Dataverse.
Experience with master data management and entity resolution, including matching customers and products across multiple systems.
Practical experience implementing security and governance, including Entra ID, row-level security, and Microsoft Purview.
Experience managing capacity and costs on a shared analytics platform.
Uses AI tools such as Copilot in day-to-day work for code generation, testing, and documentation.
Strong communication skills, with the ability to document effectively and explain technical trade-offs to non-engineering stakeholders.
Experience with product telemetry or event-driven data.
Experience preparing data for AI solutions, including retrieval, vector search, and governed access for agents (for example through MCP).
Experience with other modern data platforms and tools such as dbt, Snowflake, or Databricks, and with infrastructure as code.

Responsibilities

Design, build and run the Microsoft Fabric platform: lakehouses, warehouses, pipelines and dataflows.
Ingest and integrate data from Dynamics 365, CRM, Kantata, licensing and telemetry, using standard connectors and APIs where they fit.
Build a layered, medallion-style data model that turns raw data into certified, reusable datasets.
Resolve customer and product identities across CRM, ERP, licensing and telemetry, so every report counts the same customer once.
Monitor pipelines and automate data quality tests for completeness, freshness, uniqueness and referential integrity, with alerting and clear ownership of failures.
Manage platform capacity and cost, separating workloads and scaling only when justified.
Run source control, environments and deployment pipelines for data and BI content.
Implement access, classification, row- and column-level security, masking and privacy controls with Information Security.
Protect sensitive data such as compensation, using anonymisation and restricted workspaces.
Maintain lineage and documentation, supporting the data governance the business agrees.
Set engineering standards and coach BI developers and analysts in using them.
Work with the Enterprise Architect and R&D on integration patterns, master data and telemetry.
Prepare data for AI, exposing governed, well-described data to agents and models through controlled interfaces.