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Tier-1 brand, metro location, and broad data skillset increase applicant competition.
Skills are transferable across industries but require specific big-data and LLM experience.
Explicit 8–12 years plus 4+ years data engineering and mandatory big-data stack raise filter strictness.
Design and build AI-powered data platforms, pipelines, and applications to support sales insights and global scale data-intensive systems.
Collaborate with cross-functional teams to deliver data reports, dashboards, and ML dataset solutions aiding data-driven business decisions.
Mentor junior engineers, conduct code and architecture reviews, and drive innovation by integrating latest open-source data engineering technologies.
8-12 years total experience including at least 4 years in Data Engineering with proven delivery of large-scale solutions.
Bachelor's degree in Computer Science or related field.
Proficiency in Python or Java with knowledge of big data technologies (Delta Lake, Hive, Spark, Flink, etc.) and data architecture concepts (Data Lake, Warehouse, Medallion Architecture).
Experience with workflow orchestration tools (Airflow/Oozie) and collaborating with ML engineers, data scientists, and DevOps teams.
Senior data engineer comfortable leading end-to-end design and delivery in complex environments involving AI/LLM and big data frameworks.
Experienced collaborator interfacing with technical and non-technical stakeholders including ML teams and leadership to align data strategies.
Proactive technical mentor who keeps up-to-date with cutting-edge data engineering and AI tools and translates them into practical solutions.