Senior Data Engineer

End Date

Friday 30 October 2026

We Support Flexible Working – Click here for more information on flexible working options

Flexible Working Options

Hybrid Working

Job Description Summary

The Data Engineer will collaborate with the Data Operations, Software Engineers, Data Scientists, and Business SMEs to design, develop, integrate and test Data Product features on the product roadmaps to meet customer needs.

Job Description

Data Engineer – BAU Operations & Support

Location: India (Hybrid)

Department: Data Engineering & Operations

Experience: 8+ Years

We are looking for a proactive Data Engineer – BAU Operations & Support to manage and support enterprise data platforms, ETL pipelines, regulatory reporting solutions, and cloud-based data services. The role focuses on ensuring platform stability, resolving production issues, maintaining data quality, supporting releases, and driving operational excellence across business-critical data ecosystems.

Production Support & Incident Management

Monitor and support ETL jobs, batch processes, and data pipelines.

Investigate and resolve production incidents within agreed SLAs.

Conduct root cause analysis (RCA) and implement preventive fixes.

Support Incident, Problem, Change, and Service Request management processes.

Participate in on-call and operational support rotations as required.

Data Platform Operations

Support data warehouses, lakehouses, reporting, and regulatory data platforms.

Troubleshoot failures across databases, ETL tools, APIs, and cloud services.

Validate data loads, reconciliations, and downstream data availability.

Ensure platform reliability, performance, and operational readiness.

Monitoring & Reliability

Monitor application health, data pipelines, and infrastructure performance.

Manage alerts, dashboards, and observability tools.

Proactively identify and automate recurring operational issues.

Maintain service availability and operational KPIs.

Release & Change Support

Support production deployments and release activities.

Perform post-release validations and health checks.

Collaborate with engineering teams during hypercare and transitions.

Data Quality & Governance

Monitor data quality controls and investigate data issues.

Support regulatory, audit, security, and governance requirements.

Maintain support documentation, runbooks, and knowledge repositories.

Continuous Improvement

Develop automation scripts to reduce manual effort.

Improve monitoring, recovery, and operational processes.

Drive service stability, efficiency, and operational excellence.

Required Skills

Technical

Databases: SQL Server, Oracle, PostgreSQL, Snowflake

ETL & Integration: Azure Data Factory, SSIS, Informatica, Airflow

Cloud: Microsoft Azure, Synapse Analytics, Azure Storage

Programming: SQL, Python, PowerShell, Shell Scripting

Monitoring Tools: ServiceNow, Jira, Splunk, Dynatrace, Grafana, Azure Monitor

Functional

Production Support & Incident Management

Data Pipeline Troubleshooting

Root Cause Analysis (RCA)

Data Quality & Reconciliation

ITIL Service Management

Regulatory Reporting Support

Qualifications & Experience

Essential

4-8 years' experience in Data Engineering, Data Operations, or Production Support.

Strong SQL and troubleshooting skills.

Experience supporting enterprise data platforms and ETL processes.

Knowledge of incident, problem, and change management.

Strong analytical, communication, and stakeholder management skills.

Preferred

Banking or Financial Services experience.

Regulatory reporting platform support.

Exposure to Snowflake, Databricks, and Azure Data Platforms.

ITIL Foundation certification.

Success Measures

SLA adherence and platform availability.

Reduced incident volumes and faster resolution times.

Improved data pipeline reliability.

Successful production releases.

Increased automation and operational efficiency.

High stakeholder satisfaction.