Senior Data Engineer

End-to-End Pipeline & System Ownership: Design, build, optimize, and maintain scalable data pipelines (batch & incremental) ingesting data from Jira/JSM, OpsGenie, internal incident services, and telemetry stores.

Data Modeling & Architecture: Design and evolve reliable data models and marts (e.g., Incident Context Enriched, PIR SLAs, Hot Reviews) using modern table formats, dbt, and Databricks.

Data Quality & Pipeline Hygiene: Establish automated Data Quality (DQ) checks, anomaly detection, threshold monitoring, and P1/P2 alerting to prevent data drift and pipeline failures.

Analytics & Visualization Enablement: Partner with cross-functional teams and leadership to deliver performant, aggregation-ready datasets for dashboards (Tableau, internal tools) and executive reliability reporting.

Performance & Cost Optimization: Profile and optimize SQL/Spark/dbt queries, leverage incremental loading, and improve partitioning strategies across Databricks and Socrates datasets.

• Engineering Standards & Mentorship: Champion best practices in code reviews, CI/CD pipelines (Bitbucket Pipelines), testing, runbooks, and mentor peers across data engineering practices.