• Big data production support Role :- • Client - IBM/DBS • Mode of work - 24/7 Rotational shift (WFO) • Experience - 4-6 years • Location - Hyderabad • N.P - Immediate - 15days • Required skills:- Spark, Scala, Hive, Hadoop, SQL, Unix • Mode of interview F2F • Spark, • Scala, • Hive, • Hadoop, • SQL, • Unix Requirements Job Summary We are looking for a Big Data Support Engineer with hands-on experience in Hadoop ecosystem technologies to provide production support, monitoring, troubleshooting, and performance optimization of Big Data platforms. The candidate should possess strong analytical and problem-solving skills and be comfortable working in a support environment. Key Responsibilities • Provide L2/L3 support for Big Data applications and Hadoop clusters. • Monitor platform health, analyze logs, and proactively identify issues. • Troubleshoot production incidents and perform root cause analysis (RCA). • Support Hadoop ecosystem components such as HDFS, YARN, Hive, Spark, Kafka, Oozie, and Sqoop. • Manage job failures, performance bottlenecks, and data pipeline issues. • Work closely with development and infrastructure teams during deployments and releases. • Perform cluster maintenance, upgrades, patching, and capacity planning. • Create and maintain operational documentation, runbooks, and SOPs. • Participate in on-call support and incident management activities. • Ensure SLA compliance and timely resolution of support tickets. Required Skills • Strong experience with Hadoop ecosystem (HDFS, Hive, Spark, YARN). • Good knowledge of Kafka, Sqoop, Oozie, Flume, or NiFi. • Hands-on experience with Linux/Unix administration. • Strong SQL and data analysis skills. • Shell scripting (Bash) and/or Python scripting. • Experience with log analysis and monitoring tools. • Knowledge of Cloudera CDP/CDH or Hortonworks platforms. • Understanding of incident, problem, and change management processes. • Excellent troubleshooting and communication skills. Good to Have • Experience with Kubernetes/OpenShift. • Knowledge of Airflow, Data Engineering concepts, and ETL pipelines. • Exposure to cloud platforms (AWS, Azure, GCP). • Banking or Financial Services domain experience. • Git and CI/CD knowledge. Mandatory Skills Hadoop, HDFS, Hive, Spark, Kafka, Linux, SQL, Shell Scripting, Python, Production Support, RCA, Cloudera/CDP, Incident Management.