Data Operations / Production Support Engineer

Job Scheduling & Workflow Monitoring:
Hands-on experience with enterprise schedulers such as Control-M, Tidal, or equivalent tools

ETL Knowledge:
Strong understanding of ETL processes, data workflows, and pipeline architectures

SQL:
Proficiency in writing complex queries, debugging, and performance tuning

Shell Scripting (Bash):
Experience in writing automation scripts for operational efficiency

Linux:
Solid understanding of Linux commands, file systems, and permissions

AWS Services:
Working knowledge of AWS components including S3, EMR, and EC2

Monitor and support production data pipelines to ensure smooth and uninterrupted operations

Troubleshoot job failures and perform detailed root cause analysis (RCA)

Manage and optimize long-running jobs to improve performance and efficiency

Configure and manage job scheduling workflows and dependencies using Control-M or similar schedulers

Provide support for AWS-based data infrastructure and associated services

Collaborate with cross-functional teams to resolve incidents and ensure timely issue resolution

Strong problem-solving and analytical skills are essential

Ability to work in a fast-paced production support environment

Effective communication and coordination skills required for stakeholder interaction