Lead Data Engineer - Data Migration & Lakehouse

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Leadership: Reviewing source documentation, interviewing SMEs, producing gap analyses, and translating ambiguous or outdated specs into concrete technical requirements.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

Requirements

• 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.

What we offer

Why You'll Love Working at SQUER:

• Ownership & Responsibility: at SQUER, we believe in empowering our team. In our flat hierarchies, your ideas and actions matter more than titles. Take the reins, make an impact and grow with us.
• Learn & Grow: Tap into a € 5.000 annual training budget to sharpen your skills and take advantage of our in-house Leadership Academy. Join and be part of our active tech community through meetups, hackathons and training sessions. Get up to 40h/year additional time off for your personal education.
• Flexibility for Performance: Benefit from hybrid work options, flexible hours, workations within the EU, and additional vacation days - giving you the freedom to perform at your best.
• Tailored Tools for Success: Choose your preferred hardware configuration and leverage our suite of AI tools and licenses (Anthropic, OpenAI, and more) to suit your working style.
• A Perks-Packed Workplace: Work in a central office with a spacious terrace and BBQ, enjoy free lunch in the office, MyClubs sports membership, and either a free "Wiener Linien" ticket or a partial contribution to the "Klimaticket". Plus, benefit from free massages, referral bonuses, Corporate Benefits, and JobRad. Annual employee presents and a monthly team breakfast add extra value to your work experience.
• please refer to the application link for further information

We believe in transparent and fair compensation. For this role, the annual gross salary ranges between € 75.000 and € 95.000 - the exact placement depends on the seniority level we assess together during the process.

How to apply

apply here >>> https://www.squer.io/jobs/lead-data-engineer-data-migration-lakehouse-vie <<< Das Mindestentgelt für di...

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