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Popular data-engineer title, metro locations, and broad multi-tech requirements drive high applicant competition.
Specialized data-engineering stack and regulated-fintech preference moderately limit cross-industry transferability.
Multiple explicit multi-year requirements and mandatory specialized technologies enforce high shortlisting rigidity.
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Lead design, development, and delivery of data engineering applications using technologies like Ab Initio, Spark, Hadoop, Kafka, Oracle, and cloud platforms.
Manage and mentor a data engineering team, ensuring program delivery, code quality, and adherence to enterprise standards within an Agile environment.
Collaborate with product managers, architects, and cross-functional teams to create scalable, resilient data solutions including ETL/ELT pipelines for batch and real-time data processing.
Bachelor’s degree in Computer Science or Engineering; Master’s preferred.
6+ years hands-on experience with Hadoop cluster maintenance, optimization, data pipelines, or 8+ years relevant experience without degree.
Proficiency in Oracle, Ab Initio, Spark, Linux/Unix system administration, networking, and cloud data engineering.
Work timings: 3 PM to 12 AM IST with availability between 6 AM -11:30 AM Eastern Time for meetings. Must be open to occasional travel to regional hubs.
Experienced technical lead in data engineering within a Scaled Agile framework managing mission-critical data platform applications.
Strong expertise in building batch and real-time data pipelines, DevOps practices, and cloud migration projects (AWS preferred).
Background in financial services, especially credit card/banking/fintech domains, with exposure to sensitive data in regulated environments and proven ability to implement complex data solutions.