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Managerial data role with common tech stack requirements yields moderate candidate competition.
Medium; core data engineering skills transfer, but managerial and governance experience is important.
High technical plus managerial, governance, and specific tooling expectations increase filtering strictness.
Lead and manage a team of data engineers responsible for designing, building, and maintaining scalable, secure, and high-performance data pipelines and platforms supporting enterprise analytics and reporting.
Translate data strategy into engineering plans, ensuring high-quality, timely delivery, performance optimization, and adherence to data governance and compliance standards.
Oversee team development, financial planning (AOP, budget management, forecasting), and collaborate with stakeholders to implement data engineering solutions aligned with business needs.
College, university degree or equivalent experience in a relevant technical discipline required.
Experience analyzing business systems, data flows, and designing effective data solutions; solid background managing and transforming large data sets with scalable processing frameworks.
Hands-on experience with modern data tools such as Java, Python, Spark, Hive, Kafka, SQL, and cloud/distributed compute environments.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in leading data engineering teams delivering scalable data models, warehouses, pipelines, and analytical solutions supporting business insight.
Strong understanding of database systems, data governance, security, compliance, and performance optimization in Agile/DevSecOps environments.
Capable of strategic thinking to translate enterprise data architecture into actionable engineering initiatives and drive continuous improvement including cost optimization, scalability, and leveraging AI/co-pilot tools.