PrincipalDataPlatformEngineer

## Accountabilities Design and implement end-to-end data platform architecture, including CDC pipelines, streaming systems, schema design, transformation layers, warehouse/mart modeling, and consumption-ready datasets with infrastructure-as-code and automation-first principles. Build and maintain resilient, multi-region data systems with strong guarantees around replication, automated failover, disaster recovery, and operational reliability. Architect scalable streaming and ingestion pipelines with a focus on correctness, schema evolution, replayability, and event-driven design principles. Define and enforce data modeling standards for curated marts and semantic layers to enable reliable self-service analytics and downstream consumption. Implement comprehensive observability across the data platform, including monitoring, alerting, logging, and data quality validation frameworks. Own data governance foundations including PII classification, lineage tracking, access controls, encryption standards, and secure data handling in partnership with Security teams. Establish architectural standards and mentor engineers, driving best practices across data engineering, platform reliability, and system design. Treat cost efficiency as a core design constraint, optimizing compute and storage usage across all platform components. Requirements: 8+ years of experience in data engineering, platform engineering, SRE, or DevOps roles, with demonstrated impact at Staff or Principal IC level. Strong experience building large-scale distributed data systems in production environments with high reliability and performance requirements. Deep cloud expertise (Azure preferred, with transferable AWS or GCP experience), including infrastructure-as-code and CI/CD practices (e.g., Terraform or equivalent). Strong SQL expertise and solid data modeling skills across both streaming and warehouse/mart architectures. Hands-on experience with orchestration tools and streaming/ingestion frameworks such