The role focuses on data ingestion, monitoring, first-level debugging & troubleshooting, and ensuring stable, reliable data operations aligned with ITIL processes (Incident, Service Request, Problem, Change).

Responsibilities :

- Monitor ADF pipelines, Databricks jobs, SQL jobs, and scheduled tasks across environments (Dev/Test/Prod).

- Proactively identify failures, performance degradation, data delays, and SLA risks using Azure Monitor, Log Analytics, and platform alerts.

- Execute standard runbooks/SOPs for common failure scenarios (e. g., ADF activity retry, Databricks job restart, dependency checks).

- Log, categorise, and prioritise incidents/requests in the ITSM tool (e. g., ServiceNow/Jira) per defined SLAs.

- Perform first-level triage : review logs, identify error patterns, validate inputs, check dependencies (linked services, secrets, storage, compute).

- Resolve L1 incidents within scope; escalate to L2/L3 with complete diagnostics (error traces, pipeline run IDs, job run links, steps taken).

- Participate in Major Incident bridge calls to provide status, recovery steps, and ETA updates.

- Validate data ingestion sources (APIs, files, DB connectors) and destination readiness (tables, schemas, storage paths).

- Execute approved fixes : pipeline re-runs, job restarts, cache clear, refresh credentials (via Key Vault), validate connection strings, and re-queue tasks.

- Perform data sanity checks (row counts, schema drift, partition presence) and raise data quality issues to L2

- Maintain and update SOPs/runbooks, known error database (KEDB), and shift handover notes.

- Contribute to post-incident reviews and problem records with clear root-cause context from the L1 perspective.

- Suggest monitoring and alerting enhancements (thresholds, dashboards, auto-recovery).

- Adhere to ITIL processes for Incident, Problem, Change, and Release management.

- Follow access controls and least privilege policies; raise access requests via established channels.

- Ensure compliance with data security and privacy requirements (masking, secure secrets, audit logging).

Requirements :

- Azure Data Factory (ADF) : Monitoring pipeline runs, integration runtimes, triggers, activity logs; basic retries and dependency checks.

- Databricks : Job run monitoring, cluster status awareness, log inspection; ability to restart jobs per SOP.

- SQL (Azure SQL/Databricks SQL/Synapse) : Basic querying for validation (counts, schema checks), job status tables, and data completeness.

- Python : Read logs, understand error messages, execute/trigger simple scripts per runbook; familiarity with notebooks is a plus.

- Azure fundamentals : Storage (ADLS), Key Vault, RBAC, Log Analytics, Alerts, and Dashboards.

- Monitoring/ITSM : Azure Monitor, Log Analytics/KQL basics, ServiceNow/Jira ticketing.

Non-technical skills :

- Drive Incident/Problem resolution by assisting in key operational activities in terms of delivery, fixes, and supportability with the operations team.

- Assist in change ticket review/approvals/planning and work with internal teams.

- Assist with projects transitioning from project teams to support teams.

- Escalation points for operation-related issues

- Experience working in ServiceNow is preferred.

- Attention to detail is a must, with focus on quality and accuracy.

- Able to handle multiple tasks with appropriate priority and strong time management skills.

- Flexible about work content and enthusiastic to learn.

- Knowledge of service support, operation and design processes (ITIL)

- Ability to handle concurrent tasks with appropriate priority.

- Strong relationship skills to work with multiple stakeholders across organisational and business boundaries at all levels.

Education Qualification and Certifications required, if any :

Certifications (Preferred) :