Data Engineer

Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.

Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.

We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh.

Our generative AI-powered products are revolutionizing the practice of medicine, and we're looking for a highly motivated Data Engineer to join our growing US-based Data Engineering team. In this crucial role, you will build and optimize large scale data infrastructure to drive business decisions and machine learning research.

• Build and maintain scalable data services, pipelines and storage solutions for the feedback of unstructured application data for ML training and evaluation purposes.

• Build and manage OLAP databases, ELTs and general data tooling for analytics , business decisions and products features.

• Work closely with a team of frontend and backend engineers, product managers, and analysts.

• Optimize data infrastructure to enhance the throughput, latency and reliability of the data system.

• Investigate and correct issues identified through data operations monitors, tools, and reports.

• Designs data integrations and data quality framework.

• Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employees

• Comprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families.

• Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA.

• Paid Parental Leave: Generous paid parental leave for all full-time employees.

• Family Forming Benefits: Resources and financial support to help you build your family.

• 401(k) Matching: Contribution matching to help invest in your future.

• Personal Device Allowance: Tax free funds for personal device usage.

• Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.

• Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more.

• Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals.

• Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment.

• Compensation and Equity: Competitive compensation and equity grants for full time employees.

• ... and much more!

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• 5+ years of experience in Data Engineering or Backend Engineering with a focus on data systems.
• Proficient in at least one general purpose programming language (e.g., Python, Java, Scala) and SQL (any variant)
• Proficiency with at least one modern cloud provider (GCP, AWS, Azure) and accompanying data services
• Experience in building systems that manage the ingest, transformation, and management of both structured and unstructured data types
• Deep knowledge of modern data infrastructure best practices
• Experience with distributed systems and different distributed processing frameworks
• Experience with Terraform, Kubernetes, and containerization technologies.
• Familiarity with the deploying ML models at scale a bonus
• Experience in building data products that are well-modeled, documented and easy to understand and maintain.
• Ability to prioritize amidst changing priorities in a fast moving environment