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Strong employer brand but senior, specialized data leadership reduces applicant density.
Requires deep data engineering, regulatory, and cloud platform expertise, limiting cross-industry transferability.
Explicit 15+ years requirement plus mandatory enterprise data platform, cloud, and compliance expertise.
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Own end-to-end delivery of enterprise-scale data and UI initiatives using Agile/Scrum methodologies, including backlog prioritization and sprint execution.
Lead architecture design, development, and maintenance of scalable ETL/ELT pipelines and data infrastructure, including data warehousing, lakehouse, and big data solutions.
Manage team performance, mentor engineers, implement data quality and governance frameworks, and oversee automation, reliability, and troubleshooting of data platforms.
15+ years of experience in data engineering with leadership on enterprise-scale platforms in Agile/Scrum environments.
Hands-on experience with big data technologies such as Spark and Hadoop; proficiency in AWS cloud platform and related services (AWS Glue, EMR); knowledge of programming languages Python or Scala.
Familiarity with containerization and orchestration tools including Docker and Kubernetes.
Knowledge of data security and compliance standards such as GDPR or HIPAA.
Experienced leader skilled at managing cross-functional collaboration involving product owners, data scientists, and business teams to deliver analytics and AI/ML solutions.
Strong strategic mindset for data architecture and platform scalability in distributed systems and big data environments.
Proven ability to drive team development including mentoring, performance evaluation, and upskilling with emerging technologies like AI and ML.