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# Lead Data Engineer - Data Migration & Lakehouse

- **Company:** SQUER Solutions GmbH
- **Location:** München, Germany
- **Experience:** Expert
- **Salary:** €81,000.0
- **Contract:** Permanent contract
- **Skills:** Unity 3d, Artificial Intelligence, COBOL (Programming Language), Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Migration, Mainframes, Meta-Data Management, SQL Databases, Great Expectations (Foster Youth College-readiness and Support Program), Large Language Models, Apache Spark, Data Lakes, Entity Resolution, Data Pipelines, Legacy Systems, Databricks
- **Published:** October 15, 2026
- **Apply:** https://www.adzuna.de/details/5927563611

## About the Role

* Must-Haves
 + Migration Track Record: 5+ years in data engineering, with several large-scale legacy-to-cloud/lakehouse migrations led independently.
 + Databricks Depth: Hands-on mastery of the Databricks ecosystem - Spark, Delta Lake, Unity Catalog, Lakeflow Declarative Pipelines, and Asset Bundles for CI/CD-style deployment.
 + Data Modeling & Reconciliation: Strong command of data modeling and schema mapping across heterogeneous systems, from mainframes to legacy ERPs.
 + Discovery Experience: Experience in discovery/assessment phases end-to-end - interviewing SMEs, identifying gaps between legacy systems and target architecture, turning ambiguity into concrete requirements.
 + Data Quality Rigor: Practical experience with data quality frameworks and automated validation (e.g., Great Expectations, dbt tests, custom reconciliation tooling).
 + Communication & Risk Ownership: Ability to break down complex topics and surface risks early and clearly to both technical and non-technical stakeholders.
 + AI-Assisted Workflows: Comfort using AI/LLM-assisted tooling in a data pipeline context.

 * Nice-to-Haves
 + Experience with legacy system archaeology (undocumented COBOL/mainframe systems, EDI, proprietary ERPs)
 + Exposure to agentic AI
 + Metadata management or data catalog tooling beyond Unity Catalog
 + Experience building or evaluating LLM-based mapping/matching tools (schema matching, entity resolution)

## Description

You thrive on turning decades of legacy complexity into clean, modern data architecture. You feel at home navigating undocumented mainframes, tangled schemas, and ambiguous specs - and you know how to translate that chaos into a clear technical path forward. If you love owning complex migrations end-to-end, building trust with stakeholders through clarity and honesty, and shaping how data moves from legacy into the lakehouse era - this is for you.
Your tasks

 * Migration Ownership: Lead large-scale migration projects from legacy systems (ranging from SQL over ERP to mainframes) into modern cloud/lakehouse targets, taking full technical responsibility.
 * Databricks Architecture: Design and implement robust pipelines using Spark, Delta Lake, Unity Catalog, Lakeflow Declarative Pipelines, and Databricks Asset Bundles for CI/CD-style deployment.
 * Data Modeling & Reconciliation: Own data modeling, schema mapping, and reconciliation across heterogeneous systems, resolving structural mismatches independently.
 * Discovery & Assessment Leadership: Reviewing source documentation, interviewing SMEs, producing gap analyses, and translating ambiguous or outdated specs into concrete technical requirements.
 * Data Quality & Validation: Establish data quality frameworks and automated validation as team standards.
 * Stakeholder Communication: Proactively surface risks - documentation gaps, structural mismatches - clearly and early to non-technical stakeholders, representing SQUER with confidence.