Data Architect​/Engineer

Profession:
Database / Data science / DWH / BI

Required technologies

Data Architecture Data Engineering Data Harmonization py Spark Data Modeling Microsoft Fabric SQL

This is a hands‑on Data Architect/Engineer role focused on Customer 360 data harmonization in the automotive and industrial solutions industry. The role is split approximately 20% architecture and 80% hands‑on implementation using PySpark on Microsoft Fabric.

The position can be performed in English. Occasional travel to Nuremberg is expected every two to three months.

• Partner with business stakeholders to understand Customer 360 harmonization requirements for Accounts, Opportunities and Contacts across SAP and Salesforce.
• Translate ambiguous business definitions into a clear, documented harmonization architecture.
• Design the end‑to‑end harmonization solution on Microsoft Fabric Lakehouse, including raw, staging, trusted and semantic medallion layers.
• Define surrogate keys, self‑referencing account hierarchies, deduplication rules and cross‑system bridge keys.
• Build and maintain harmonization logic hands‑on in PySpark notebooks on Fabric, including key normalization and reconciliation, deterministic deduplication, hierarchy explosion and cross‑system joins.
• Define and resolve grain, 1:
  
  N cardinality and entity‑resolution rules so downstream facts and semantic models join correctly and reproducibly.
• Parameterize solutions for multiple environments and help promote them from sandbox to development, testing and production.
• Perform validation, smoke tests and data‑quality checks.
• Document architecture decisions, mapping rules and data contracts.
• Provide harmonization design guidance to data engineers and testers.

Background and experience

• University degree in business informatics, computer science or a comparable qualification, or alternative training combined with relevant professional experience.
• At least five years of professional experience in data engineering and/or data architecture, including designing and delivering data harmonization, master‑data or customer‑data integration solutions.

Technical skills

• Proven experience designing end‑to‑end medallion‑architecture data platforms from raw through staging and trusted to semantic/gold layers, and translating them into working pipelines.
• Strong hands‑on programming skills in PySpark and SQL, with the ability to build production harmonization logic personally.
• Hands‑on experience with Microsoft Fabric Lakehouse architecture, including Delta tables, notebooks, schemas, semantic models, Direct Lake, One Lake Security RBAC and RLS; experience with Azure Synapse or Databricks is also relevant if combined with willingness to work in Fabric.
• Data‑modeling expertise for harmonization, including surrogate‑key design, self‑referencing hierarchies, deterministic deduplication and grain/cardinality resolution.
• Experience building semantic models and Power BI Direct Lake star schemas on top of a Lakehouse.
• Experience integrating and reconciling heterogeneous source systems such as SAP customer hierarchies and Salesforce/CRM, including cross‑system key reconciliation, bridge keys and entity resolution.
• Proficient understanding of distributed and cloud‑computing principles, preferably Microsoft Azure, including Fabric, Synapse, Data Lake and Data Factory/Pipelines.
• Experience parameterizing solutions across sandbox, development, testing and production environments and promoting them through Git‑based CI/CD.
• Experience with agentic data engineering, for example using Git Hub Copilot Agents in Visual Studio Code to generate Fabric artifacts.

Additional skills

• Domain knowledge of SAP customer/account master data, including customer hierarchies and harmonized…