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Tier-1 brand plus data role demand, but seniority and Databricks specialization limit applicant density.
Core Databricks, Spark and cloud skills are transferable, though senior finance/regulatory context increases sensitivity.
Explicit 15+ years requirement plus mandatory Databricks, Spark, cloud, and leadership skills.
Lead end-to-end delivery and governance of data engineering platforms with a focus on Databricks and cloud architectures.
Own solution architecture design ensuring scalable, secure, high-performing data solutions aligned to business outcomes.
Lead cross-functional global teams bridging business stakeholders, architects, and engineering for delivery excellence.
15+ years of technology delivery experience with leadership exposure.
Strong hands-on expertise in Databricks, Spark (Python/Scala), and cloud platforms (AWS/Azure).
Proven experience in enterprise-scale data architecture, data engineering, and big data ecosystems (Hadoop, Spark, Databricks).
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Experienced leader capable of managing large-scale data modernization and transformation programs.
Technically strong with deep expertise in data pipeline automation, CI/CD, and data governance in cloud environments.
Comfortable leading globally distributed teams and coordinating across multiple stakeholders including business and engineering functions.