Senior Systems Engineer (4 - 7 years of experience in Hadoop DevOps, Python, SQL, Shell scripting)

About this role

About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters – to you, to your community, and to the world

Progress starts with you. Job Description Role Overview We are seeking a Systems Engineer with strong experience in Hadoop and Big Data platform operations. The ideal candidate will have hands-on expertise with Hadoop ecosystem components, automation using Shell/Bash and Python, and experience supporting large-scale data pipelines and distributed systems

This role will be responsible for provisioning, maintaining, monitoring, scaling, and troubleshooting Hadoop clusters, as well as supporting automation, CI/CD processes, QA validation triggers, and operational improvements across Big Data platforms. Responsibilities Develop and maintain Shell/Bash scripts and Python-based automation scripts to streamline platform operations and improve overall efficiency. Automate recurring platform and data operations, including: Pipeline execution Data validation triggers Job scheduling and orchestration Log collection and monitoring Alerting and notification workflows Environment health checks Data archival processes Deployment activities Design and implement automation solutions for new data job onboarding, configuration updates, infrastructure maintenance, and routine operational tasks

Support the automation, deployment, and operational management of Apache Spark based ETL pipelines, data processing jobs, and Big Data workloads. Integrate automated QA validation checks into pipeline execution workflows to ensure data accuracy, comple

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