Senior Observability Engineer - Datadog with Splunk

• Build a full Splunk dashboard inventory with priority ranking, then perform SPL-to-Datadog field-level mapping and gap analysis.

• Execute dashboard-by-dashboard migration with fidelity validation, parallel run and sign-off before Splunk deprecation, keeping operational disruption to a minimum.

• Establish governance and role-based access control for the new observability platform.

• Design and build executive and operational dashboards across case volume, throughput, SLA, error and capacity trends, sourced from Datadog, Salesforce, AWS/CloudWatch and Pharma Co-vigilance application logs.

• Configure automated refresh, threshold-breach and anomaly alerting, and deliver adoption assets (user guide, KPI definition document, metric glossary).

• Expose Datadog log data to the AI incident-triage agent via integration.

• Sustain 99.5%+ dashboard availability post-migration.

Must-have skills:

• 6–10 years in observability/SRE tooling; deep Datadog (dashboards, monitors, log pipelines, RBAC, integrations)

• Strong Splunk and SPL authoring and reverse-engineering, AWS/CloudWatch telemetry

• Strong knowledge on API/connector-based data integration

• KPI workshop facilitation with executive stakeholders.

• Nice to have — Datadog certification, Splunk Power User/Admin, Salesforce Reports & Dashboards, Confluence-based documentation, GxP/21 CFR Part 11 validated-environment experience.