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Mid-tier IT firm and a common senior data-engineer profile produce moderate competition with limited senior supply.
Core data engineering skills transfer across industries, but senior cloud and big-data experience increases specificity.
Explicit 8–12 years and mandatory cloud, ETL, and big-data skills increase shortlisting strictness.
Design, develop, and manage scalable data platforms and enterprise data solutions.
Build modern data platforms to support advanced analytics, business intelligence, and AI/ML initiatives.
Enable data-driven decision-making across the organization through robust data engineering practices.
8–12 years of experience in data engineering roles.
Strong expertise in data engineering, cloud technologies, ETL/ELT development, data warehousing, and big data ecosystems.
Work Experience Required: 8–12 years in relevant data engineering.
Notice Period: Not explicitly mentioned in the JD.
Experienced in building and managing scalable enterprise data platforms suited for complex analytics needs.
Familiar with cloud-based data solutions and big data ecosystems supporting AI/ML workflows.
Senior-level candidate with proven ability to drive data engineering projects impacting business intelligence and decision-making.