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.