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Senior, niche Databricks-Snowflake platform role at a well-known enterprise yields moderate competition.
Core data-platform and cloud skills are transferable, though healthcare governance adds moderate domain bias.
Strict technical and seniority requirements including 12+ years and Databricks, Snowflake, Spark, AWS, Python mandate tight filters.
Lead design and delivery of scalable, secure, and high-performance enterprise data platforms using AWS, Databricks, Snowflake, Spark, and Python.
Own development and optimization of batch, streaming, CDC, event-driven data pipelines, and AI-ready data products including RAG and agentic AI capabilities.
Drive engineering excellence through CI/CD, Infrastructure as Code, security, observability, governance, mentoring, and end-to-end data product/platform ownership.
12+ years of experience in software and/or data engineering with large-scale production data platform delivery.
Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, IT, or equivalent experience.
Expertise in Python, SQL, Apache Spark (PySpark), Databricks, Delta Lake, Snowflake, and AWS cloud-native data architectures.
Experience with CI/CD, automated testing, monitoring, data governance, security controls, and practical exposure to Generative AI technologies including RAG, embeddings, vector search, and agentic workflows.
Senior-level engineer with deep hands-on expertise in modern cloud data platform technologies across AWS, Databricks, Snowflake, and Spark ecosystems.
Experience translating complex business and technical requirements into scalable, secure, and automated data solutions with operational ownership.
Proven ability to lead and mentor engineering teams with strong governance, security, and performance orientation in enterprise environments.