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Tier-1 brand and Hyderabad metro raise applicant density despite senior, specialized Big Data requirements.
Core Big Data and cloud skills are broadly transferable, though insurance domain knowledge is beneficial.
Explicit 8+ years requirement and mandatory Big Data/Azure technical skills enforce strict filters.
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Design, build, and maintain scalable ETL/ELT pipelines on Azure cloud or on-premises for large volumes of structured and unstructured data supporting batch and real-time processing.
Ensure data pipeline reliability, performance, security, data quality, and compliance with policies and standards.
Collaborate with cross-functional partners including Business, Technology, Data Governance, Data Science and DevOps to deliver production-grade data and analytics solutions.
8-11+ years of relevant big data engineering experience.
Bachelor’s degree in computer science, information technology, or equivalent.
Strong skills in SQL, Python/Scala, NoSQL (HBase, Cosmos DB), and big data frameworks like Apache Spark, Hadoop, Hive.
Hands-on experience with Azure cloud services (Data Factory, Eventhub, Functions, Synapse, Databricks) and building real-time and batch streaming pipelines.
Proven ability to operate independently as an individual contributor in a senior big data engineering role.
Experience working in enterprise-scale environments integrating with diverse data and analytics teams, including data governance, modeling, science, and business partners.
Familiarity with advanced data engineering architectures like Medallion architecture, and operational practices including DevOps, CI/CD pipelines on Azure DevOps.