Lead Data Engineer

We are seeking a Lead Data Engineer to support a large-scale healthcare data platform initiative focused on modernizing data ingestion, automation, and semantic layer capabilities within Google Cloud Platform (GCP).

This role will play a critical part in building scalable, reliable, and business-ready data solutions that enable enterprise analytics and reporting across the organization.

The ideal candidate brings strong hands-on engineering expertise, deep knowledge of cloud-native data platforms, and experience leading technical implementation efforts in complex enterprise healthcare environments.

What You’ll Do Design, build, and optimize scalable data pipelines supporting enterprise healthcare analytics and reporting use cases Lead automation efforts across ingestion, transformation, orchestration, and operational monitoring workflows Develop and maintain ingestion frameworks for structured and semi-structured healthcare data sources Build and expand semantic data layers within GCP and BigQuery to support consistent, trusted business reporting and analytics consumption Design scalable ELT/ETL workflows leveraging modern cloud-native architecture patterns Partner closely with architects, analytics teams, and business stakeholders to translate data requirements into scalable technical solutions Optimize BigQuery performance, partitioning, and cost management strategies Implement engineering best practices for testing, observability, reliability, and deployment automation Support data governance, data quality, and metadata management initiatives across the platform Mentor junior engineers and provide technical leadership across delivery teams Required Skills Strong expertise in Google Cloud Platform (GCP), particularly: BigQuery Cloud Storage Cloud Composer / orchestration tooling Dataflow or modern ingestion frameworks Experience designing and building scalable data ingestion and pipeline automation frameworks Strong understanding of semantic layer development and