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Tier-1 bank, mid-level generic Data Engineer in Pune with broad stack and strong brand drives high competition.
Requires financial services experience and specific big-data stack, reducing cross-industry transferability.
Multiple mandatory big-data technologies and financial services experience make shortlisting strict.
Design, develop, and deliver key components of big data engineering solutions involving Hadoop, Spark, and cloud infrastructure.
Lead Level 3 support for technical infrastructure, including debugging, troubleshooting production incidents, and supporting Level 2 teams.
Drive continuous improvements, perform code reviews, write unit tests, manage deployments, and ensure adherence to architectural standards and integration strategies.
Bachelor’s degree in Computer Science, Software Engineering, or equivalent with minor in Finance, Mathematics, or Engineering.
Relevant Financial Services experience is mandatory.
Proficiency in Java/Scala, Spark, Hadoop Hive, workflow orchestrators (e.g., Airflow), and scripting languages (Python/Bash/Shell).
Work Experience Required: Not explicitly mentioned in the JD. Location: Pune, India.
Experienced in managing complex big data applications in production and non-production environments, including cloud (preferably GCP) and Infrastructure as Code.
Strong familiarity with SDLC tools and processes such as HP ALM, Jira, Service Now, Agile, and release/deployment management.
Able to leverage AI tools to optimize workflows responsibly, with robust analytical and communication skills, and capability to assist junior team members.