Imagen Technologies - Staff Data Engineer, AI Data Platform
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Requirements
• Mission-driven and passionate about building foundational technology to improve healthcare. • 5+ years of hands-on experience in data engineering, or software engineering with a data focus. • 5+ years of hands-on experience in data engineering • 2+ years of experience in a senior or lead role, with a proven track record of owning technical roadmaps and making significant architectural decisions. • 2+ years of experience in a senior or lead role • Expert-level proficiency in Python and a deep understanding of data structures and algorithms. Mastery of SQL is also required. • Expert-level proficiency in Python • Deep expertise with at least one major cloud provider (AWS, GCP, Azure) and proven experience designing and managing solutions in a cloud-native environment. • Deep expertise with at least one major cloud provider (AWS, GCP, Azure) • Hands-on experience with modern data stack technologies, such as: • Workflow orchestration tools (e.g., Airflow, Prefect, Dagster). • Large-scale data processing frameworks (e.g., Spark, Dask). • Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation). • Containerization technologies (e.g., Docker, Kubernetes). • Demonstrated experience designing and managing data lakes, data warehouses, or petabyte-scale object storage systems (e.g., S3, GCS). • BS in Computer Science or a related field, or equivalent real-world experience. • Experience working in a multi-cloud environment and managing cross-cloud data transfer and cost optimization. • Experience with MLOps or building infrastructure that directly supports the machine learning lifecycle. • Familiarity with healthcare data standards and regulations (e.g., HIPAA, DICOM, FHIR). • Direct experience engineering solutions for diverse medical imaging modalities (e.g., CT, MR, XR, Ultrasound). • Experience building systems in a regulated or compliance-heavy industry. • Imagen Technologies is a remote-first company and this job is conducted remotely. • The base salary for the position is between $190,000-$215,000, plus equity and benefits. Please note that the range is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location.
Responsibilities
• Architect and Own the AI Data Platform: You will take full ownership of the technical roadmap and architecture for our multi-petabyte, multi-cloud data platform. Your primary goal will be to ensure our AI teams have reliable, scalable, and performant access to high-quality medical data. • Architect and Own the AI Data Platform: • Build and Scale Data Pipelines: Design, build, and maintain robust data ingestion, processing, and transformation pipelines for billions of medical images (e.g., DICOM) and clinical reports. You'll focus on creating systems that are automated, observable, and efficient. • Build and Scale Data Pipelines: • Evaluate, select, and implement a modern workflow orchestration solution (e.g., Airflow, Prefect, Dagster) to manage our end-to-end data pipelines for medical image processing. • Evaluate, select, and implement a modern workflow orchestration solution • Champion Data Quality and Governance: Implement and enforce rigorous data quality frameworks, validation checks, and security protocols. As the steward of our most sensitive data, you will ensure all aspects of the platform are secure and compliant with standards like HIPAA. • Champion Data Quality and Governance: • Lead Technical Strategy and Best Practices: Establish and champion best practices in data engineering, DataOps, and infrastructure management. You will make key decisions on tooling and technology, driving the technical direction for all data-related initiatives. • Lead Technical Strategy and Best Practices: • Partner with the AI Team: Serve as the primary technical partner and subject matter expert for our AI and research teams. You will collaborate closely with them to understand their data requirements and build solutions that accelerate their model development lifecycle. • Partner with the AI Team:
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