Big Data Developer

• 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

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.