Key skills
Amazon RedshiftAWSAzureBigQueryETLGoogle Cloud PlatformJenkinsLinuxPythonScalaShell ScriptingSparkSQLUnixShellELTData EngineeringSnowflakeRedshiftGCPGoogle CloudAzure DevOpsGitCI/CD
About this role
Role Overview
- Design, develop, and manage enterprise-scale batch scheduling and data pipeline workflows
- Develop and support data pipelines using ETL/ELT tools and scripting
- Monitor, troubleshoot, and optimize batch failures and performance issues
- Schedule and monitor workloads in AWS / Azure / GCP environments
- Integrate Control-M with data platforms such as Snowflake, Redshift, BigQuery, etc.
- Collaborate with application, data, and infrastructure teams to ensure seamless scheduling
Requirements
- 10+ years of experience in Data Engineering
- 5+ years of hands-on experience as a Control-M Developer / Scheduler
- Strong experience in Data Engineering or ETL development
- Proficiency in Unix/Linux shell scripting
- Strong SQL skills for data validation and troubleshooting
- Experience supporting enterprise batch processing environments
- Experience with Python, Spark, or Scala
- Knowledge of CI/CD tools (Git, Jenkins, Azure DevOps)
- Control-M certification is a plus
Tech Stack
- Amazon Redshift
- AWS
- Azure
- BigQuery
- ETL
- Google Cloud Platform
- Jenkins
- Linux
- Python
- Scala
- Shell Scripting
- Spark
- SQL
- Unix
Benefits
- All your information will be kept confidential according to EEO guidelines.