Descripción
1 Lead Data Engineer - Data Migration & Lakehouse from now 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Leadership: Reviewing source documentation, interviewing SMEs, producing gap analyses, and translating ambiguous or outdated specs into concrete technical requirements.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. Your Qualifications * 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). ** Communic