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Niche Databricks specialization and senior (12y) experience reduces applicant density.
Databricks and cloud data engineering skills transfer across industries, but require specialized platform expertise.
Explicit 12-year total, 7 years Databricks, and deep tech/leadership requirements enforce strict filtering.
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Design, optimize, and manage end-to-end data pipelines on Databricks platform leveraging Spark, Delta Lake, and Unity Catalog.
Lead cloud data solutions architecture and migrate legacy data warehouses to modern lakehouse architectures on Azure, AWS, or GCP.
Lead and mentor engineering teams, conduct technical design reviews, and engage customers through technical discussions and solution walkthroughs.
12 years total professional experience with at least 7 years in Databricks and cloud data engineering.
Deep expertise in Databricks technologies including Unity Catalog, Photon engine, Databricks SQL, Spark, Delta Lake.
Proven experience architecting and implementing scalable data solutions on Azure, AWS, or GCP cloud platforms.
Experience mandatory in advanced ETL/ELT pipeline design, data modeling, performance tuning, and large-scale data warehouse modernization.
Location: Hybrid work arrangement.
Employment Type: Full-time.
Senior engineer with multi-team leadership experience delivering enterprise data solutions using Databricks and cloud platforms.
Strong technical architect capable of designing scalable data pipelines, optimizing performance, and migrating legacy warehouses to lakehouses.
Experienced in customer engagement and technical stakeholder management within complex enterprise environments.