Application Support Engineer - IBM DataStage

Our client is a rapidly growing, aut70000omation-led service provider specializing in IT, business process outsourcing (BPO), and consulting services. With a strong focus on digital transformation, cloud solutions, and AI-driven automation, they help businesses optimize operations and enhance customer experiences. Backed by a global workforce of over 32,000 employees, our client fosters a culture of innovation, collaboration, and continuous learning, making it an exciting environment for professionals looking to advance their careers.

Committed to excellence, our client serves 31 Fortune 500 companies across industries such as financial services, healthcare, and manufacturing. Their approach is driven by the Automate Everything, Cloudify Everything, and Transform Customer Experiences strategy, ensuring they stay ahead in an evolving digital landscape. 

As a company that values growth and professional development, our client offers global career opportunities, a dynamic work environment, and exposure to high-impact projects. With 54 offices worldwide and a presence in 39 delivery centers across 28 countries, employees benefit from an international network of expertise and innovation. Their commitment to a 'customer success, first and always' philosophy ensures a rewarding and forward-thinking workplace for driven professionals.

We are currently searching for an Application Support Engineer — IBM DataStage (ETL/Application Support):

Responsibilities

• Provide daily production support for ETL processes built with IBM InfoSphere DataStage and related application components.
• Monitor DataStage jobs and ETL schedules, ensuring successful data delivery and operational stability.
• Respond to incidents and service requests via ticketing systems (e.g., ServiceNow), troubleshoot failures, and restore services within SLAs.
• Perform root cause analysis on recurring issues and implement preventive and corrective actions.
• Deploy and maintain DataStage jobs and related artifacts in test and production environments under established change control processes.
• Optimize performance of DataStage jobs by tuning job design, parallelism, and resource usage.
• Maintain and update runbooks, operational checklists, and job documentation.
• Collaborate across teams (developers, BI, DBAs, infrastructure, and business stakeholders) to resolve integration or performance issues.
• Validate data quality and reconciliation between source and target systems, escalating anomalies when necessary.
• Manage scheduling tools (Control-M, AutoSys) and resolve scheduler-related problems.
• Create and maintain automation scripts (shell scripting, Python, etc.) for operational efficiency.
• Participate in on-call rotations and support after-hours incidents or scheduled maintenance.
• Contribute to deployment planning, testing, and rollback strategies for ETL changes.

Requirements

• Strong hands-on experience with IBM InfoSphere DataStage (ETL job monitoring, troubleshooting, deployment, and performance tuning).
• Proficiency in SQL for data validation and debugging.
• Experience using ticketing systems (e.g., ServiceNow) for incident and change management.
• Familiarity with scheduling/orchestration tools such as Control-M or AutoSys.
• Experience scripting in Unix/Linux environments (shell, Python preferred).
• Solid understanding of ETL concepts, data quality, and reconciliation.
• Excellent communication and analytical skills, with a proactive problem-solving mindset.

Desired 

• Experience with data warehousing environments or BI ecosystems.
• Knowledge of data governance, metadata management, or data lineage tools.
• Exposure to cloud ETL platforms (e.g., Azure Data Factory, AWS Glue) is a plus.

Languages

• Advanced Oral English.
• Native Spanish.

Note:

• Fully remote.

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• Strong hands-on experience with IBM InfoSphere DataStage (ETL job monitoring, troubleshooting, deployment, and performance tuning).
• Proficiency in SQL for data validation and debugging.
• Experience using ticketing systems (e.g., ServiceNow) for incident and change management.
• Familiarity with scheduling/orchestration tools such as Control-M or AutoSys.
• Experience scripting in Unix/Linux environments (shell, Python preferred).
• Solid understanding of ETL concepts, data quality, and reconciliation.
• Excellent communication and analytical skills, with a proactive problem-solving mindset.