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Tier-1 employer, popular data-engineer title, metro location and broad modern data-stack requirements increase competition.
Data engineering skills are transferable, but enterprise AI/scale and cloud experience favors similar industries.
Explicit 8+ years, leadership expectation and mandatory cloud/data-stack skills enforce strict shortlisting.
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Lead design and hands-on engineering of large-scale data lakes, pipelines, and infrastructure for AI and business intelligence.
Own scalability, reliability, and efficiency of internal data ecosystem platforms integrating data, AI applications, and core infrastructure.
Translate business objectives into scalable architectures and enforce technical standards for quality, governance, and performance across data engineering projects.
8+ years of experience in data engineering.
Proficiency in a programming language such as Python, Scala, or Java, and strong SQL skills.
Experience designing and operating large-scale data pipelines on cloud platforms (AWS, GCP, or Azure).
Work Experience Required: Minimum 8 years in data engineering roles.
Experienced in leading cross-functional data engineering projects from concept to production.
Skilled in building scalable, high-throughput data pipelines supporting AI and advanced analytics.
Operates at the intersection of data engineering and AI infrastructure with strong architectural and problem-solving capabilities.