8–10 yrsBengaluruOn-siteDirect career pageEst. 20–30 LPA
Posted 22h ago
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Job description
Structured overview of role & requirements
About This Role
- Lead requirement gathering and interaction with business stakeholders to define functional specifications.
- Design, develop, and optimize data pipelines and applications using Hadoop ecosystem (HDFS, MapReduce, YARN, Hive, Sqoop, Spark) and Azure cloud services (ADLS, ADFS, ADF).
- Monitor and optimize cluster performance, job workloads, and query efficiency using Cloudera Manager and related tools; conduct code reviews with developers.
Minimum Requirements
- 8 to 10 years of work experience.
- Proven hands-on expertise in Hadoop ecosystem components (HDFS, MapReduce, YARN, Hive, Sqoop, Spark) and Azure cloud technologies (ADLS, ADFS, ADF).
- Strong experience with Spark application development using DataFrame API, Spark SQL, Scala, and Python in Databricks environment.
- Bachelor's or Master's degree in Engineering (BTech/MTech).
Ideal Candidate Profile
- Experienced in developing and optimizing metadata-driven ingestion pipelines using Azure Data Factory and ETL processes from on-premises to cloud data storage.
- Skilled in advanced Hive management including table types, join techniques, partitioning, bucketing, and performance optimization.
- Comfortable monitoring and troubleshooting big data clusters and queries, with experience in performance dashboards and workload management tools (e.g., Cloudera Manager, Workload XM).