Senior Data Engineer

Role: Senior Data Engineer

Background:

Leveraging data analytics to provide insights and recommendations to drive strategic decision-making collaborating with cross-functional teams, including Finance, Accounting, Operations, HR, and others to deliver accurate and timely financial reporting, dashboards, analytics, and data-driven insights.

Key Accountabilities

A Senior Data Engineer (Production Support) will be responsible for monitoring, maintaining, and supporting ETL processes, data pipelines, and data warehouse environments. The ideal candidate should have strong troubleshooting skills, hands-on experience with ETL tools, and the ability to quickly resolve production issues to ensure data availability, accuracy, and reliability.

• Monitor and support daily ETL processes, data pipelines, and batch jobs to ensure timely and accurate data delivery.
  
• Troubleshoot and resolve production issues, job failures, and performance bottlenecks across ETL and data warehouse systems.
  
• Work Closely with Data platform team to resolve data load issues.
  
• Perform root cause analysis of recurring issues and implement permanent fixes.
  
• Collaborate with development teams to transition projects smoothly into production and ensure operational readiness.
  
• Implement and maintain monitoring, alerting, and logging solutions for proactive issue detection.
  
• Ensure data quality, consistency, and availability through ongoing validation and health checks.
  
• Apply best practices for production support, including incident management, change management, and problem management.
  
• Work closely with business users, data analysts, and other stakeholders to resolve data-related queries.
  
• Document runbooks, support procedures, and knowledge base articles to streamline production operations.
  
• Continuously optimize processes for reliability, performance, and scalability in production environments.
  
• Ensure compliance with data security, access controls, and audit requirements in production systems.
  
  Day-to-Day Tasks - Senior Data Engineer (Production Support)
  
  Production Support:
  
  
• Check system dashboards, logs, and alerts for failures or anomalies.
  
• Verify data quality and integrity checks (row counts, duplicates, missing data, schema changes).
  
• Review ETL/ELT job runs, data pipeline executions, and batch processes.
  
• Validate data loads into staging, warehouse, and downstream systems for critical tables.
  
• Monitor real-time and scheduled jobs to ensure SLAs are met.
  
• Investigate and resolve production issues (job failures, data inconsistencies, performance delays).
  
• Collaborate with business users to resolve data access or reporting issues.
  
• Coordinate with development/engineering teams for fixes, hot patches, or re-runs of failed jobs.
  
• Track and document incidents, resolutions, and preventive measures in ticketing systems (e.g., ServiceNow, Jira).
  
• Participate in daily/weekly operations meetings to report status and highlight issues.
  
• Handover critical ongoing issues to on-call/offshore support (if applicable).
  
  Minor Works/ Maintenance:
  
  
• Enhance Existing models with addition of fields as per the requirements.
  
• Help with Deployments and initial loads during Go-live.
  
• Perform root cause analysis for recurring or high-severity incidents.
  
  Proactive/Preventive Work:
  
  
• Fine-tune ETL workflows and SQL queries to improve performance.
  
• Implement monitoring scripts and automation to reduce manual intervention.
  
• Restructure the Load plans to improve effeciency.
  
• Review security and access controls to ensure compliance.
  
• Update documentation (runbooks, troubleshooting guides, SOPs) for operational continuity.
  
  Skills and Capability requirements:
  
  
• 6+ years of experience with ETL, data pipelines, and data warehouse production environments.
  
• Strong expertise in troubleshooting ETL/ELT processes using tools such as Matillion, Informatica, ODI, or SSIS.
  
• Experience in cloud-based data platforms like Snowflake.
  
• Proven ability to analyze job failures, perform root cause analysis, and implement permanent fixes.
  
• Hands-on experience with monitoring, alerting, and logging tools.
  
• Familiarity with incidents, problem, and change management processes in ITIL-based environments.
  
• Strong SQL programming and debugging skills with relational and cloud databases.
  
• Experience with traditional and non-traditional forms of analytical data design (Kimbal, Inmon etc)
  
• Excellent communication skills to interact with business users, analysts, and cross-functional technical teams.
  
  Nice to Have
  
• Domain knowledge in the area of finance data is preferred.
  
• Experience with SAP Systems and Databases
  
• Knowledge of data visualization tools, such as PowerBI or Tableau