HIKE2

• Design and build large-scale data platforms on Databricks (Delta Lake, Spark, Unity Catalog) in Azure • Develop and maintain batch and streaming data pipelines for high-volume, complex data sources • Implement medallion/lakehouse architectures from the ground up in greenfield environments • Build and optimize data models to support analytics, reporting, and downstream applications • Integrate Databricks with enterprise systems (APIs, event streams, warehouses, ML workflows) • Tune Spark jobs and pipelines for performance, reliability, and cost at scale • Support production deployments, including CI/CD pipelines, testing, and release management • Partner directly with enterprise clients to translate requirements into working technical solutions • Collaborate with architects, engineers, and data scientists across multiple workstreams • Balance speed and quality, knowing when to move fast and when to harden solutions • Make pragmatic decisions in ambiguous, evolving environments (especially greenfield builds) • Contribute hands-on while also guiding design and approach across the team • Communicate tradeoffs clearly to both technical and non-technical stakeholders • Work within modern engineering practices (version control, code reviews, automated testing) • Demonstrated ability to mentor and guide data engineers and analysts

• Design and build large-scale data platforms on Databricks (Delta Lake, Spark, Unity Catalog) in Azure • Develop and maintain batch and streaming data pipelines for high-volume, complex data sources • Implement medallion/lakehouse architectures from the ground up in greenfield environments • Build and optimize data models to support analytics, reporting, and downstream applications • Integrate Databricks with enterprise systems (APIs, event streams, warehouses, ML workflows) • Tune Spark jobs and pipelines for performance, reliability, and cost at scale • Support production deployments, including CI/CD pipelines, testing, and release management