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Metro role with broad, in-demand data platform skills but non-Tier-1 employer and senior level.
Core data platform skills transfer across industries, though healthcare domain and HIPAA knowledge increase specialization.
Explicit 10+ years, required management experience, and specific data platform tech stacks enforce strict filtering.
Own the strategy, architecture, and execution of the enterprise data platform to enable reliable, scalable, and secure data pipelines supporting analytics, reporting, and AI/ML.
Lead and grow the Data Platform team, managing sprint planning, backlog prioritization, and delivery cadence.
Collaborate with cross-functional teams including product, engineering, analytics, and data science to deliver high-impact data solutions and enforce data governance and quality standards.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or related field.
10+ years of hands-on data engineering experience, including at least 5 years in a people management role leading data platform or infrastructure teams.
Proficiency with cloud data platforms such as AWS (Redshift, Glue, S3, EMR, Lambda), Snowflake or Databricks and orchestration tools (Apache Airflow, Prefect) and streaming platforms (Kafka, Kinesis).
Strong expertise in data warehousing, data modeling, ETL/ELT design, data governance, metadata management, and data quality frameworks.
Experienced leader in data platform engineering capable of managing and growing high-performing technical teams.
Deep expertise in cloud-native big data technologies with ability to design scalable, fault-tolerant data pipeline architectures.
Background or familiarity with healthcare domain data (claims, enrollment, care management) and regulatory standards (HIPAA, PHI) is highly valued but not mandatory.