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Senior Big Data Engineer Pyspark Databricks (Pune)

Citi · Pune

📅 11/08/2026
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We are looking to hire experienced Data engineer to join our team responsible for building technology solutions for the Markets Business Control Tech and for various business risk and controls functions. You will work with the Architects, Business stakeholders and Data Scientists to ensure we are meeting their requirements to develop and drive automation. This is an exciting opportunity to work on an important project for the group, which will have huge impact on the business and future design in this area. Key Responsibilities: Evaluate and provide technical solutions to solve a variety of complex and interdependent processes. Build and maintain the platform ensuring timely delivery of work items across the multiple initiatives/components. Ensure all team members adhere to our code quality and testing standards. Test and debug programs Coordinate with internal teams to understand user requirements and provide technical solutions. Utilize knowledge of applications development procedures and concepts, and basic knowledge of other technical areas to identify and define necessary system enhancements, including using script tools and analysing/interpreting code Consult with users, clients, and other technology groups on issues, and recommend programming solutions, install, and support customer exposure systems Apply fundamental knowledge of programming languages for design specifications. Analyze applications to identify vulnerabilities and security issues, as well as conduct testing and debugging Identify problems, analyze information, and make evaluative judgements to recommend and implement solutions Resolve issues by identifying and selecting solutions through the applications of acquired technical experience and guided by precedents Has the ability to operate with a limited level of direct supervision. Skills & Experience : Experience Professional with 13+ Years of experience in Data engineering with valuable exposure on spark architecture Good Exposure on PySpark , Sp .
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