Data Engineer (Production Support) - Inside IR35

Our Client are looking for a Senior Data Engineer (Production Support) who 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.

The role will require 1-2 days per week onsite in Warwickshire.

Day-to-Day Tasks - 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.

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 analyse 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)