Data Engineer

• 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 the 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.
• 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.
• Participate in daily/weekly operations meetings to report status and highlight issues.
• Handover critical ongoing issues to on-call/offshore support (if applicable).
• Enhance existing models with the 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.
• 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 efficiency.
• Review security and access controls to ensure compliance.
• Update documentation (runbooks, troubleshooting guides, SOPs) for operational continuity.

Technologies:

• Cloud
• Data Warehouse
• ETL
• Informatica
• Support
• ITIL
• ODI
• SAP
• SQL
• Security
• Snowflake
• SSIS
• Tableau
• JIRA
• ServiceNow, We are seeking a Senior Data Engineer to join our dynamic team where we leverage data analytics to provide insights and recommendations that drive strategic decision-making. Our ideal candidate will be responsible for monitoring, maintaining, and supporting critical ETL processes, data pipelines, and data warehouse environments. We offer a collaborative work environment with opportunities to work with cross-functional teams in Finance, Accounting, Operations, and HR. This role is essential in ensuring the datas availability, accuracy, and reliability in our cloud-based data platforms. Join us in this exciting opportunity to enhance our data capabilities!

• 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
• Domain knowledge in the area of finance data is preferred
• Experience with SAP Systems and Databases is a plus
• Knowledge of data visualization tools, such as PowerBI or Tableau is a plus