Big Data Support

Location: Bengaluru, Karnataka, India

Experience: 5+ years

Employment Type: Full-time

As a Big Data Support Engineer, you will be responsible for the operational support, performance monitoring, troubleshooting and maintenance of our big data platforms and pipelines. You will work closely with engineering, infrastructure, platform and business teams to ensure high availability, reliability and scalability of our data ecosystem.

• Provide 24x7 (or as required) support for production big data environments: incident management, root cause analysis, problem management, change implementation, recovery/resiliency planning.
• Monitor, alert, and manage health of big data clusters (Hadoop/Spark/YARN/etc.), identify bottlenecks, capacity constraints, and performance tuning opportunities.
• Work with Linux/Unix administration, scripting (shell, Python/Perl) to automate routine tasks, build monitoring/observability dashboards.
• Handle cluster and service upgrades, patching, configuration changes in coordination with platform/infrastructure teams.
• Support data ingestion, transformation and processing workflows; collaborate with data engineering and analytics teams for onboarding new workloads.
• Ensure adherence to operations best-practices (ITIL/Change/Incident/Problem/Configuration management) and enforce compliance/security standards (access control, encryption, audit).
• Provide documentation of processes, runbooks, standard operating procedures; train junior team members or less experienced staff.
• Liaise with stakeholders (business users, QA, development, vendors) for issue resolution and service improvement.
• Participate in on-call rotations, after-hours emergencies, and weekend support if required.

• Bachelor’s degree in Computer Science, Information Technology or related discipline (Master’s preferred).
• Minimum 5 years of experience in production support or operations of big data environments.
• Solid hands-on experience with Hadoop ecosystem (HDFS, YARN, MapReduce, Hive, Spark, Impala, Oozie, Kafka) or similar big data frameworks. Citi Careers+2Citi Careers+2
• Strong experience with Linux/Unix system administration and shell / scripting languages (bash, Python, Perl) for automation. Citi Careers+1
• Good SQL skills and experience with relational and/or big data databases. Adzuna+1
• Experience with production support frameworks: incident/problem/change management, capacity/availability monitoring, cluster health/observability tools (e.g., Grafana, ELK stack, Splunk). Citi Careers+1
• Ability to analyse performance bottlenecks, do capacity planning, tune large-scale clusters and resource usage. Citi Careers+1
• Excellent communication and interpersonal skills; able to work with cross-functional teams and with business stakeholders in a fast-paced environment. Citi Careers
• Willingness to work flexible hours, occasional weekends/after-hours support, as production environments are critical.

• Certifications in Big Data (e.g., Cloudera Certified Administrator) or relevant cloud/data engineering credentials.
• Hands-on experience with cloud big data platforms (AWS EMR, Azure HDInsight, GCP Dataproc).
• Experience with workflow schedulers (Control-M, Autosys) and orchestration. Citi Careers
• Knowledge of security technologies in big data (Kerberos, Ranger, Sentry) and encryption/access control. SmartRecruiters+1
• Familiarity with DevOps/CI/CD practices for data infrastructure, containerisation (Docker/Kubernetes) or automation tools.
• Experience in large global enterprise/financial services domain is a plus.

• Opportunity to work in a cutting-edge data platform environment supporting large volumes of data and mission-critical workloads.
• Exposure to emerging technologies, performance tuning, and operational excellence.
• A collaborative team culture with continuous learning and growth opportunities.
• Bengaluru location, modern office, hybrid/remote flexibility (if applicable).

Please send your CV along with details of your hands-on experience with:

• Big data clusters supported (size, tech stack)
• Incidents you handled and how you resolved them
• Automation or performance improvements you implemented
• Your support/operations shift experience