Up to 9 years of IT experience & 5 Years on Hadoop and K8s Eco Systems
Last 3 years of relevant experience in banking/financial services industry
Demonstrable analytical skills with deep knowledge of Big Data Ecosystem in a Production Support Environment.
Hands On Experience within the Hadoop Tool Sets Hive Hue Spark Kafka Kudu Flink Ozone Kafka and Streaming.
Strong SQL Python Java and Unix shell scripting
Incident problem and service Outage management experience is Plus.
Good Communication and Articulation Skills
Roles/Responsibilities
Strong in data engineering concepts and programming
Experience in building and optimizing big data data pipelines architectures and data sets.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Strong analytic skills related to working with unstructured datasets.
Experience in supporting data transformation data structures metadata dependency and workload management.
Working knowledge of message queuing stream processing and highly scalable big data data stores.
Provide operational support and ensure SLI of Applications
Troubleshoot Batch Issues & root causes to Mitigate Impacts to SLA
Proactively Identify and Identify opportunities for preventive Maintenance
Perform Administration & Optimization to achieve of Optimal System Performance
Conduct review of technical and functional solutions from enhancement/project team to ensure they conform to Established Standards
Recommend Design and Operational Optimizations
Respond on time to the queries raised by various business units
Provide Timely updates (Status Progress Issues Resolutions) to Business Stakeholders
Work with Project/Enhancement Teams to Review Transition for Run Team
Participate in Disaster Recovery and Business Continuity exercises
Support relevant software/platform/database upgrade for the systems
Knowledge of Troubleshooting Core Java Python Scala spark batch API and streaming applications
Support data APIs data science ML applications running on Kubernetes platform
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