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Tier-1 brand, mid-level generalist data role, metro location, broad tech stack increases candidate competition.
Core big-data and cloud skills are highly transferable across industries with low domain bias.
Explicit 5-8 years plus mandatory big-data and cloud tech stack creates strict shortlisting filters.
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Design, build, and maintain ETL/ELT pipelines on Azure cloud or on-premises for large volumes of batch and real-time structured and unstructured data.
Monitor, optimize, and troubleshoot data pipelines ensuring reliability, scalability, performance, and adherence to data quality and security standards.
Collaborate with cross-functional teams including Business, Technology, Operations, and Data & Analytics capabilities to deliver production-grade data and analytics solutions.
5-8+ years of relevant experience in big data engineering.
Bachelor’s degree in computer science, information technology or equivalent.
Mandatory technical skills include SQL, Python/Scala, NoSQL and distributed databases (HBase, Cosmos DB), Apache Spark, Hadoop, Hive, Azure Data Factory, Eventhub, Azure Functions, Synapse, Databricks.
Work Experience Required: 5-8+ years; Notice Period: Not explicitly mentioned in the JD.
Experienced in developing both batch and real-time data processing and streaming pipelines using Big Data frameworks and Azure cloud services.
Capable of independently handling end-to-end pipeline development and ensuring data governance compliance in a global technology setup.
Proficient in stakeholder engagement and collaboration with various teams in a complex data & analytics environment, exhibiting strong analytical and structured problem-solving skills.