Senior DataOps Engineer: Production Data & Scheduling Lead

Sun Life; Taguig; Sur place; PHP 1 200 000 - 2 400 000; Plein temps

Résumé du poste

Sun Life Philippines in Metro Manila, Taguig invites a seasoned DataOps/ETL Operations professional to join our IT - Application Development team. You will operate, monitor and continuously improve production data workloads serving SLHK, manage schedules and SLAs, and support data quality checks with complete evidence.

The role requires 8+ years of experience and 3–6 years in DataOps/ETL operations, with hands-on use of enterprise schedulers (e.g., Control-M) and solid SQL and cloud data

Qualifications

• 8+ years of experience in IT or data ops roles.
• 3–6 years in DataOps/ETL operations; hands-on with enterprise schedulers.
• Working SQL and cloud data familiarity; exposure to data quality, lineage and metadata is a plus.

Responsabilités

• Scheduling & Monitoring — Own daily/weekly schedules in the enterprise scheduler; maintain calendars/dependencies; implement health checks and alerts (e.g., Control‑M).
• Incident & Problem Management — Triage and restore service; capture RCA and prevention actions; maintain runbooks/knowledge base.
• Change & Release Execution — Execute deployments/config changes under change controls with evidence and rollback plans.
• Data Quality Operations Support — Run DQ checks and reconciliations, file evidence, and track remediation with DG/DQ leads.
• Service Reporting — Publish job success/latency/SLA compliance; automate to reduce manual toil.

Connaissances

DataOps experience

ETL operations

SQL

Cloud data familiarity

Outils

Control-M

Description du poste

Sun Life Philippines in Metro Manila, Taguig invites a seasoned DataOps/ETL Operations professional to join our IT - Application Development team. You will operate, monitor and continuously improve production data workloads serving SLHK, manage schedules and SLAs, and support data quality checks with complete evidence.

The role requires 8+ years of experience and 3–6 years in DataOps/ETL operations, with hands-on use of enterprise schedulers (e.g., Control-M) and solid SQL and cloud data