Role Overview
We are looking for a highly skilled Lead GCP Data Engineer with AI expertise to design, build, and optimize scalable data platforms on Google Cloud. This role requires strong data engineering fundamentals, leadership experience, and hands-on expertise in leveraging AI-assisted engineering tools to accelerate development and innovation.
Key Responsibilities
- Lead the design, development, and deployment of scalable data pipelines and architectures on GCP
- Drive end-to-end ETL/ELT pipeline development for large-scale data processing
- Provide technical leadership and mentorship to a team of data engineers, ensuring quality and best practices
- Leverage AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, Claude) to improve productivity and code quality
- Collaborate with stakeholders to deliver secure, scalable, and high-performance data solutions
- Optimize query performance and cloud costs across storage and compute
- Establish and maintain CI/CD pipelines and DataOps practices
Must-Have Skills & Experience
- 9–12 years of experience in data engineering with a proven track record of delivering large-scale data solutions
- Strong expertise in Data Engineering using Python, SQL, and GCP cloud platforms
- Proven experience in ETL/ELT pipeline development and large-scale data processing
- Hands-on experience with GCP services such as BigQuery, Cloud Storage, Dataflow, Pub/Sub, and Cloud Composer
- Practical knowledge of AI-assisted engineering tools such as GitHub Copilot, ChatGPT, Claude, or similar platforms
- Strong experience in CI/CD and DataOps practices (Git, Jenkins, GitHub Actions, automated deployments)
- Proven ability to lead teams, mentor engineers, and collaborate with cross-functional stakeholders
Good-to-Have Skills
- Experience with Healthcare data platforms, including Clinical Trials, EMR/EHR systems
- Familiarity with healthcare data standards and regulatory environments
