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Strong employer brand and generalist data-engineer title balanced by seniority and Snowflake specialization.
Requires enterprise healthcare PHI experience and Snowflake/Databricks expertise, reducing cross-industry portability.
Multiple mandatory senior technical skills and explicit 9+ years make filters strict.
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Design and maintain canonical data models and scalable data pipelines leveraging Snowflake and cloud platforms to support analytics, AI, and ML workloads.
Implement and optimize data governance, data quality, observability, and performance frameworks across data pipelines and platforms.
Enable AI/ML capabilities by structuring data for advanced use cases and deploying AI-powered solutions using no-code and low-code platforms.
Bachelor's degree in Computer Science, Engineering, Data Engineering, or related technical field (or equivalent experience).
9+ years of experience in software and data engineering with enterprise-scale data platform design and delivery.
Hands-on experience with Snowflake, Databricks, cloud data platforms (Azure and/or GCP), SQL, and Python.
Proven expertise in ETL/ELT frameworks, batch and streaming processing, data governance, and hybrid cloud/on-premises data architectures.
Experienced in designing high-volume, high-availability data pipelines optimized for performance and cost in enterprise environments.
Skilled collaborator with Analytics, BI, Data Science, and Product teams to deliver trusted and reusable data assets.
Strategic operator comfortable with complex data governance, observability, and compliance (including PHI/PII) requirements in healthcare or regulated sectors.