Senior Resiliency Platform Engineer

This role combines insurance technology knowledge, service catalog and CMDB expertise, observability tooling, and production-grade automation. The work involves helping map complex insurance technology structures into a technical service catalog while improving data quality, matching, and adoption of shared platforms and standards across engineering teams.

• Apply insurance domain knowledge to understand how insurance carriers structure technology around lines of business and map that structure to a technical service catalog while preserving meaningful business distinctions.

• Work with Datadog Service Catalog, APM tagging conventions, and monitor configuration.

• Work with ServiceNow CMDB data, including cmdb_ci_service and relationship tables.

• Evaluate data quality, matching heuristics, and the reliability and limitations of data across systems.

• Drive the adoption of shared tooling or standards across engineering teams through incentive design and low-friction onboarding.

• Support phased, metrics-driven platform or framework rollouts across multiple independent teams.

• Build and maintain production-grade Python automation for data matching and ETL processes.

• Develop automation involving fuzzy matching, scoring, and join logic across heterogeneous data sources.

• Strong experience in the insurance domain, including understanding how insurance carriers structure technology around lines of business and mapping that structure onto a technical service catalog without flattening meaningful business distinctions.

• Strong experience with Datadog and ServiceNow.

• Hands-on experience with Datadog Service Catalog, APM tagging conventions, and monitor configuration.

• Experience with ServiceNow CMDB, including cmdb_ci_service and relationship tables, with the ability to reason about data quality, matching heuristics, and where each system's data can and cannot be trusted.

• Strong experience rolling out platform or framework adoption, including helping engineering teams adopt shared tooling or standards through incentive design and low-friction onboarding.

• Experience running phased, metrics-driven rollouts across multiple independent teams.

• Strong experience in Python and automation.

• Ability to build and maintain production-grade data-matching and ETL pipelines involving fuzzy matching, scoring, and join logic across heterogeneous sources.

• Experience with GitLab, including CI Visibility and project/group tagging.

• Experience with Backstage or similar internal developer portals.

• Familiarity with service dependency mapping.

• Familiarity with system-of-record and provenance patterns in a catalog or CMDB context.

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