Lead Data Engineer - Data Migration & Lakehouse

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Description

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Leadership: Reviewing source documentation, interviewing SMEs, producing gap analyses, and translating ambiguous or outdated specs into concrete technical requirements.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 confide

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