Job Description
Location: Culver City, CA (4 Days Onsite)
Experience: 8–10 Years
Job Summary
We are looking for an experienced Lead DataStage Integration Support Engineer to drive end-to-end ownership of the ETL platform, including development, administration, and production support. This role requires a strong technical leader who can ensure platform stability, optimize performance, and lead continuous improvement initiatives across enterprise data integration systems.
Key Responsibilities
- Lead and mentor a team of DataStage support engineers
- Own end-to-end ETL platform delivery including development, administration, and support
- Design, develop, and enhance ETL jobs and workflows
- Administer DataStage environments including user roles, security, deployments, and migrations
- Troubleshoot and resolve job failures across DataStage and Unix/Linux environments
- Drive incident management processes, root cause analysis (RCA), and preventive measures
- Develop and maintain shell scripts and Python-based automation solutions
- Manage job scheduling and monitoring tools, including handling failures and optimizing workflows
- Configure and maintain batch jobs, calendars, and workload scheduling policies
- Support integration processes including file transfers, mapping configurations, and data workflows
- Collaborate with cross-functional teams and external vendors for issue resolution
- Define, implement, and enforce best practices for ETL development, deployment, and support
Required Skills & Qualifications
- 8–10 years of experience in IBM DataStage (Development and Administration)
- Strong expertise in Unix/Linux, shell scripting, and cron jobs
- Hands-on experience with Python programming
- Solid experience with enterprise job scheduling and workload automation tools
- Strong knowledge of relational databases such as SQL Server and Oracle
- Proven experience in production support, incident management, and RCA processes
- Demonstrated experience in team leadership and stakeholder communication
Preferred Qualifications
- Experience working in large-scale enterprise data environments
- Strong problem-solving and analytical skills
- Ability to manage multiple priorities in a fast-paced environment