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Senior role but popular data-platform skills and broad tech requirements increase applicant density.
Core data platform skills are transferable, though healthcare/regulatory experience increases sensitivity.
Explicit 8+ years, 2+ years leadership, and concrete AWS/Spark/Kafka platform requirements.
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Lead design, evolution, and scaling of AWS-based enterprise data platform for analytics, AI-enabled solutions, and business decision-making.
Architect and implement scalable, secure data platforms; define technical vision, architecture standards, and engineering best practices.
Hire, mentor, and develop data engineering team; collaborate with stakeholders to build data products that drive measurable business outcomes.
8+ years in Data Engineering or related fields; 2+ years leading engineering teams.
Proven experience building and scaling enterprise data platforms on AWS using tools like S3, Redshift, Glue, Lambda, Kinesis.
Strong expertise in data architecture, modeling, distributed data processing, Spark, Kafka, Airflow.
Demonstrated track record delivering measurable business value via data engineering and AI/ML capabilities.
Technical leader with combined expertise in data engineering, architecture, and product mindset to solve business problems.
Experience evaluating and implementing modern data architectures including AI-ready platforms and metadata-driven designs.
Strong at balancing hands-on execution with strategic architectural leadership and stakeholder management across technical and business teams.