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Tier-1 brand and metro location increase competition, but senior Databricks specialization narrows candidate pool.
Requires deep Databricks, Spark, cloud, and data architecture expertise, limiting cross-industry transferability.
Explicit 15+ years, Databricks expertise and architecture leadership are mandatory, making filters strict.
Lead end-to-end delivery of data engineering and analytics platforms with strong governance using Databricks and cloud technologies.
Own solution architecture design to ensure scalable, secure, high-performance data platforms aligned to business outcomes.
Manage global cross-functional teams and act as liaison between business stakeholders, architects, and engineering for delivery alignment and reporting.
15+ years of technology delivery experience with strong leadership in Data Engineering and Big Data ecosystems.
Expertise in Databricks, Spark (Python/Scala), data lakehouse architecture, and cloud platforms (AWS or Azure).
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Experience in CI/CD, DevOps, and end-to-end data pipeline automation.
Experienced in leading large-scale data modernization or transformation programs with enterprise-scale architecture design.
Strong technical owner comfortable with both hands-on coding and high-level architecture decisions involving distributed teams.
Proven ability to implement governance frameworks and deliver on cross-regional stakeholder management in global organizations.