• Design and implement end-to-end data pipelines (ETL/ELT) that ingest, process, and curate large-scale enterprise data, including telemetry/vehicle data and other structured/unstructured sources. • Migrate and modernize data assets to a centralized data platform (e.g., BigQuery) using principled data lake/warehouse architectures (Bronze/Silver/Gold or Medallion architecture) to power analytics and reporting. • Architect scalable data models and data warehouses, optimizing for query performance, maintainability, and cost efficiency. • Develop and operate robust orchestration pipelines using Airflow/Astronomer or Schedule Query, with secure, reproducible CI/CD workflows (Terraform + Git). • Build and maintain reliable data quality checks, lineage, and monitoring with observability tools (e.g., Splunk, Looker/Grafana/Tableau/Power BI dashboards) to rapidly detect and resolve data issues. • Implement data governance, security, and compliance controls (data lineage, access controls, PII/PHI protection) in collaboration with security and privacy teams. • Lead the design and delivery of analytics-ready data assets for cross-functional teams, including dashboards, alerts, and self-service analytics. • Mentor and coach junior engineers, review code, and drive best practices in data engineering, testing, and documentation. • Collaborate with data scientists, product managers, and business stakeholders to translate requirements into scalable data solutions and timely insights. • Monitor cost and capacity planning for cloud resources; optimize storage and compute usage across GCP services (BigQuery, Dataflow, Dataproc, GCS). • Participate in on-call rotations and incident response to maintain high availability of data services.