2 months ago
Base Salary
$170k - $185k/yr
Responsibilities
- Lead system design reviews and provide recommendations.
- Architect and implement scalable data ingestion pipelines.
- Develop reusable, configuration-driven, containerized pipeline components.
- Collaborate with cross-functional teams to meet data requirements.
- Design and maintain data transformation pipelines using dbt.
- Build monitoring and alerting systems for data ingestion processes.
- Apply software engineering best practices to data infrastructure.
- Mentor junior engineers and promote coding standards.
- Champion AI-assisted development across the team.
- Identify opportunities to automate repetitive engineering work.
- Author and support high-quality technical documentation.
Requirements
- 10+ years of experience in data engineering focused on large-scale data ingestion.
- Proven track record of building automated ETL processes using Python and DBT SQL.
- Strong understanding of ETL/ELT frameworks and distributed data processing.
- Hands-on experience with AI coding tools and directing AI agents.
- Experience with healthcare data standards and regulatory environments.
- Ability to handle and process varied file types, including healthcare standards.
- Extensive background in designing scalable data architectures in AWS.
- Solid grounding in software engineering principles.
- Familiarity with containerization technologies like Docker and Kubernetes.
- Strong communication skills for partnering with technical and non-technical stakeholders.
Benefits
- Dynamic role with opportunities for learning and growth.
- Collaboration with experienced clinicians, engineers, and digital health entrepreneurs.