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Tier-1 brand, broad big-data skillset, popular role title and metro/hybrid location drive high competition.
Big-data engineering skills are transferable, but BFSI domain knowledge and people leadership raise sensitivity to medium.
Explicit 10–12 years plus deep big-data, cloud and leadership requirements make shortlisting highly strict.
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Design, build, and maintain scalable ETL/ELT pipelines on Azure cloud or on-prem for large volumes of structured and unstructured data.
Lead solution design, estimation activities and independently manage end-to-end data engineering for production-grade data analytics solutions.
Provide people leadership by coaching, developing, and engaging a team in data and analytics talent development.
10-12+ years of relevant experience in data engineering or related fields.
Bachelor's degree in computer science, information technology, or equivalent.
Proficient in SQL, Python/Scala, big data frameworks (Apache Spark, Hadoop, Hive), and Azure cloud platform (Data Factory, Eventhub, Synapse, Databricks).
Experience with ETL pipeline design, performance tuning, DevOps practices (Git, Azure DevOps, CI/CD), and expertise in real-time and batch data processing.
Experienced in end-to-end data pipeline ownership with ability to lead design, solutioning, and estimation independently.
Strong leadership and mentorship skills with proven ability to develop and engage data engineering talent.
Familiarity with BFSI domain, Medallion architecture, real-time streaming pipelines, and emerging technologies like Gen AI tools is preferred.