Company:A Large Global Organization
Key Skills: Pyspark, AWS, Databricks, SQL, Data Engineer, Informatica, Git, Datastage, Python, Oracle, Shell
Roles and Responsibilities:
Develop and maintain automation scripts to improve operational workflows for data platforms.
Troubleshoot production issues across Databricks and ETL pipelines, ensuring timely resolution.
Support and optimize data processing jobs using PySpark and SQL in cloud-based environments.
Collaborate with engineering teams to automate repetitive operational tasks and reduce manual effort.
Contribute to reliability improvements by identifying recurring incidents and driving corrective actions.
Skills Required:
11-13 years of relevant experience in data engineering and operational support for distributed systems
PySpark for building and maintaining Spark-based data processing workloads.
AWS experience supporting data platform operations and cloud services.
SQL expertise for querying, debugging, and validating data pipelines.
Databricks experience supporting enterprise data engineering and production support.
Positive to Have:
Informatica experience for ETL development and pipeline support.
Shell scripting, Oracle, Python, IBM DataStage, and Git for broader platform coverage.
Education: Any Graduation