Big Data Support Engineer

Responsibilities

• Monitor and provide operational support for production applications, ensuring service levels and application availability are maintained.
• Troubleshoot batch processing failures and production issues, perform root cause analysis (RCA), and implement corrective actions to minimize business and SLA impacts.
• Analyse internal and external data using SQL to investigate issues, resolve business queries, and identify process improvement opportunities.
• Perform production support activities using Unix/Linux shell scripting for troubleshooting, automation, and operational tasks.
• Manage and respond to incidents, problems, and service outages, ensuring timely resolution and minimal disruption to business operations.
• Proactively identify recurring issues and recommend preventive maintenance measures to improve application stability and performance.
• Respond promptly to queries and support requests raised by various business units.
• Provide regular status updates on incidents, progress, issues, and resolutions to business stakeholders.
• Participate in Disaster Recovery (DR) and Business Continuity (BCP) exercises to ensure operational readiness.
• Work with job scheduling tools to monitor and manage batch job execution and dependencies.

Requirements

• 3–4 years of experience in IT, preferably in Production Support or Application Support.
• Strong analytical and troubleshooting skills with hands-on experience in a production support environment.
• Strong knowledge of SQL for data analysis, querying, and issue investigation.
• Hands-on experience with Unix/Linux commands and shell scripting.
• Understanding of Incident Management, Problem Management, and Service Outage Management.
• Familiarity with Teradata or Hadoop.
• Exposure to job scheduling tools such as Control-M, Autosys, or equivalent.
• Understanding of batch processing, production monitoring, SLA management, and application support operations.
• Good communication, stakeholder management, and articulation skills.
• Ability to work in a time-sensitive production environment and manage multiple priorities effectively.