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Generalist data manager role with common tech stack and likely metro hiring increases candidate competition.
Core data engineering and tooling skills are broadly transferable across industries with low domain lock-in.
Managerial ownership plus mandatory data engineering stack, governance, and budgeting experience creates stringent shortlisting filters.
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Lead and manage a team of data engineers responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support enterprise analytics and reporting.
Translate data strategy and architecture into actionable engineering projects ensuring high-quality, timely delivery and adherence to data governance, security, and compliance standards.
Oversee team development, performance optimization, budget management, and continuous improvement initiatives focused on data pipeline scalability, cost-efficiency, and automation including AI/Co-pilot tooling.
College degree or equivalent in a relevant technical discipline or equivalent experience.
Experience managing and transforming large data sets using scalable processing frameworks with hands-on development skills in Java, Python, Spark, Hive, Kafka, SQL, or related cloud-native technologies.
Experience implementing and supporting data pipelines in cloud or distributed environments and working with large-scale data movement/integration tools.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced leader with a strong background in scalable data engineering solutions across cloud/distributed compute environments and proven ability to optimize data models and pipelines for business insights.
Skillful in applying data governance, security, compliance principles, and modern engineering practices such as Agile, DevSecOps, CI/CD, and infrastructure as code.
Demonstrated capability to drive continuous improvement in data engineering processes, enable self-service pipeline capabilities, and leverage AI/Co-pilot technologies to boost engineering productivity.