Lead design and delivery of scalable data platforms on Google Cloud Platform (Google Cloud Platform).
Own end-to-end data architecture using BigQuery, Cloud Storage, Dataflow, and Pub/Sub.
Build and optimize batch and streaming pipelines for high-volume, high-velocity data.
Define data modeling, partitioning, and performance optimization best practices.
Lead a team of data engineers; provide technical guidance, reviews, and mentorship.
Collaborate with product, analytics, and ML teams to translate business needs into data solutions.
Implement data quality, validation, monitoring, and observability frameworks.
Ensure security, governance, and compliance using IAM, DLP, and encryption standards.
Drive CI/CD, automation, and infrastructure-as-code using Terraform and Cloud Build.
Optimize cost and performance across Google Cloud Platform services and data workloads.
Establish standards for coding, testing, documentation, and release management.
Troubleshoot complex data issues and lead root-cause analysis efforts.
Evaluate and introduce new Google Cloud Platform services and modern data engineering tools.
Partner with stakeholders to define roadmaps, SLAs, and data platform strategy.
Required: 8+ years in data engineering, strong Google Cloud Platform expertise, leadership experience preferred.
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Healthcare Data Engineering Lead (Google Cloud Platform) || Remote || Contract Summary: Strong experience architecting enterprise data platforms on Google Cloud (Google Cloud Platform). The architect will work as a strategic technical partner to design and build a Google Cloud Platform BigQuery-based Data Lake & Data Warehouse ecosystem. The role requires deep hands-on expertise in data ingestion, transformation, modeling, enrichment, and governance, combined with a strong understanding of clini
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