- 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.