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Strong brand, popular data engineering role, broad skillset and likely metro location increase applicant competition.
Core data engineering skills are widely transferable across industries despite BFSI being nice-to-have.
Explicit senior experience requirement, specific Azure/Databricks/Spark stack and mentorship expectations raise filter strictness.
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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 in batch and real-time environments.
Monitor and optimize data pipeline performance ensuring reliability, security, compliance, and data quality standards are met.
Mentor Data Engineers and independently lead design, solutioning, and estimation efforts while collaborating across multiple technical and business teams.
8-10+ years of relevant Big Data engineering experience.
Bachelor's degree in Computer Science, Information Technology or equivalent.
Expertise in Big Data frameworks (Apache Spark, Hadoop, Hive), Azure cloud services (Data Factory, Eventhub, Synapse, Databricks), ETL pipeline design, and programming in SQL and Python/Scala.
Experience with data security, compliance, and quality standards; mentorship experience in Data Engineering roles.
Senior-level individual contributor comfortable working independently on full cycle data engineering solutions with end-to-end ownership.
Strong cross-functional collaborator skilled in stakeholder engagement and translating complex technical solutions into business value.
Deep expertise in Azure data ecosystem and big data architectures including medallion architecture, real-time streaming pipelines, and performance tuning.