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Data Engineer (Staff/Senior) - job 1 of 2

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.

The Role

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.

What You'll Do

  • 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.

Who You Are

  • 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

Base Salary: $200,000 USD - $265,000+ USD per year + Equity

The salary range provided is based on transparent pay guidelines and is an estimate for candidates residing in the San Francisco and New York City metro areas. The actual base salary will vary depending on the candidate's location, relevant experience, skills, qualifications, and other job-related factors. Additionally, this role may include the opportunity to participate in a company stock option plan as part of the total compensation package.

Must be willing to work from our SF office at least 3x per week

This position requires a commitment to a hybrid work model, with the expectation of coming into the office a minimum of (3) three times per week. Relocation assistance is available for candidates willing to move to San Francisco.

Must be willing to travel up to 10%

Abridge typically hosts a three-day builder team retreat every 3-6 months. These retreats often feature internal hackathons, collaborative project sessions, and social events that allow the team to connect in person.

We value people who want to learn new things, and we know that great team members might not perfectly match a job description. If you’re interested in the role but aren’t sure whether or not you’re a good fit, we’d still like to hear from you.

Why Work at Abridge?

  • Be a part of a trailblazing, mission-driven organization that is powering deeper understanding in healthcare through AI!

  • Opportunity to work and grow with talented individuals and have ownership and impact at a high-growth startup.

  • Flexible/Unlimited PTO — Salaried team members can take off as much approved time off as they need, plus 13 paid holidays

  • Equity — For all salaried team members

  • Medical insurance — We pay 100% of the premium for you + 75% for dependents. 3 Aetna plans to choose from.

  • Dental & Vision insurance — We pay 100% of the premium for you + 75% for dependents. 2 Aetna plans to choose from.

  • Flexible Spending (FSA) & Health Savings (HSA) Accounts

  • Learning and Development budget — $3,000 per year for coaching, courses, workshops, conferences, etc.

  • 401k Plan — Contribute pre-tax dollars toward retirement savings.

  • Paid Parental Leave — 16 weeks paid parental leave, for all full-time employees

  • Flexible working hours — We care more about what you accomplish than what specific hours you’re working.

  • Home Office Budget — We provide up to $1,600 in a one-time reimbursement to set up your home office.

  • Sabbatical Leave — 30 days of paid Sabbatical Leave after 5 years of employment.

  • ...Plus much more!

Life at Abridge

At Abridge, we’re driven by our mission to bring understanding and follow-through to every medical conversation. Our culture is founded on doing things the “inverse” way in a legacy system—focusing on patients, instead of the system; focusing on outcomes, instead of billing; and focusing on the end-user experience, instead of a hospital administrator's mandate.

Abridgers are engineers, scientists, designers, and health policy experts from a diverse set of backgrounds—an experiment in alchemy that helps us transform an industry dominated by EHRs and enterprise into a consumer-driven experience, one recording at a time. We believe in strong ideas, loosely held, and place a high premium on a growth mindset. We push each other to grow and expose each other to the latest in our respective fields. Whether it’s holding a PhD-level deep dive into understanding fairness and underlying bias in machine learning models, debating the merits of a Scandinavian design philosophy in our UI/UX, or writing responses for Medicare rules to influence U.S. health policy, we prioritize sharing our findings across the team and helping each other be successful.

Diversity & Inclusion

Abridge is an equal opportunity employer. Diversity and inclusion is at the core of what we do. We actively welcome applicants from all backgrounds (including but not limited to race, gender, educational background, and sexual orientation).

Staying Safe - Protect Yourself From Recruitment Fraud

We are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article. Please exercise caution and cease communications if something feels suspicious about your interactions. 

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CEO of Abridge
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Shivdev Rao
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Average salary estimate

$232500 / YEARLY (est.)
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$200000K
$265000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Data Engineer (Staff/Senior), Abridge

At Abridge, we're on a mission to revolutionize healthcare through our innovative AI-powered platform, and we're looking for a Data Engineer (Staff/Senior) to join our vibrant team in San Francisco! In this exciting role, you'll be at the forefront of transforming patient-clinician conversations into structured clinical notes that enhance care and improve efficiencies. Your primary duties will include building and scaling data services, pipelines, and storage solutions that support machine learning research and help drive critical business decisions. Collaborating with a talented team of engineers and product managers, you'll develop OLAP databases and ensure that our data infrastructure is optimized for performance and reliability. We believe in empowering our engineers, so not only will you be fixing data issues and designing quality frameworks, but you'll also be actively contributing to the strategic direction of our data systems. We're looking for candidates who have a robust background in data engineering, proven experience with modern data infrastructure, and a passion for building meaningful data products. If you're excited about the potential of generative AI in healthcare and want to be a part of something impactful, we would love to hear from you! Plus, you can enjoy a fantastic benefits package, including equity options, flexible PTO, and a supportive work environment focused on growth and collaboration.

Frequently Asked Questions (FAQs) for Data Engineer (Staff/Senior) Role at Abridge
What are the main responsibilities of a Data Engineer at Abridge?

As a Data Engineer (Staff/Senior) at Abridge, your main responsibilities include building and maintaining scalable data services, designing data quality frameworks, and managing OLAP databases. You'll optimize data infrastructure to enhance throughput and reliability while working closely with cross-functional teams to support machine learning and business analytics.

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What qualifications do I need to become a Data Engineer at Abridge?

To be considered for the Data Engineer (Staff/Senior) position at Abridge, you should have over 5 years of experience in Data Engineering or Backend Engineering, proficiency in programming languages such as Python or Java, and experience with cloud platforms like AWS or GCP. Knowledge of modern data infrastructure best practices and previous experience with distributed systems are essential as well.

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What does the team culture look like for Data Engineers at Abridge?

The team culture for Data Engineers at Abridge emphasizes collaboration, growth, and a commitment to innovation. You'll be working alongside diverse professionals from various backgrounds and disciplines, participating in team retreats, and engaging in ongoing learning opportunities that foster both personal and professional development.

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What benefits does Abridge offer for Data Engineers?

Abridge offers a comprehensive benefits package for Data Engineers that includes competitive salaries, equity options, flexible/unlimited PTO, fully covered medical and dental insurance, a generous learning and development budget, and much more. Additionally, you have the chance to participate in a hybrid work model, enjoying both remote and in-office work.

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How does the Data Engineer role contribute to Abridge's mission in healthcare?

The Data Engineer (Staff/Senior) role at Abridge plays a critical part in our mission to empower better healthcare through AI. By developing robust data infrastructure and systems, you'll ensure that our AI-generated outputs are reliable and trustworthy, directly enhancing clinicians' ability to provide quality care to their patients.

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Common Interview Questions for Data Engineer (Staff/Senior)
Can you explain your experience with building scalable data services?

When answering this question, focus on specific projects where you've designed data services or pipelines. Mention the technologies used and highlight your role in optimizing these systems to handle large volumes of data efficiently.

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What programming languages are you proficient in for data engineering tasks?

Provide details on the programming languages you are comfortable with, such as Python, Java, or Scala. Explain how you have used these languages for data manipulation, ETL processes, or building data pipelines in previous roles.

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How do you ensure quality and reliability in your data pipelines?

Discuss the strategies you employ to maintain data quality, such as implementing monitoring solutions, conducting data validation checks, and employing rigorous testing before deployment. Highlight any tools or frameworks you commonly use.

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Describe a challenging data issue you encountered and how you resolved it.

Choose a specific challenge that illustrates your problem-solving skills. Describe the problem, the approach you took to diagnose it, and the steps you implemented to resolve it, emphasizing the impact of your solution.

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What experience do you have with cloud data services?

Detail your experience with cloud platforms like AWS, GCP, or Azure. Talk about the specific data services you've used, how you've integrated them into your workflows, and any projects where they played a crucial role.

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Can you explain your understanding of OLAP databases?

Demonstrate your knowledge of OLAP databases by clarifying their purpose in analytics and reporting. Discuss your experience in designing or managing OLAP systems and the types of queries or analysis you've conducted.

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How do you optimize data infrastructure for performance?

Speak about techniques you’ve used to enhance data throughput and minimize latency, such as indexing, partitioning, or caching strategies. Highlight specific examples where your optimizations led to measurable improvements.

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What frameworks have you used for distributed processing?

Mention frameworks like Apache Spark, Hadoop, or others that you've worked with. Describe the projects in which these frameworks were employed and how they benefited your data processing capabilities.

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How do you handle changing priorities in a fast-moving environment?

Explain your approach to prioritization, emphasizing communication with stakeholders, time management techniques, and flexibility. Share examples of situations where you've successfully adapted to shifting priorities.

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What are the key best practices for managing both structured and unstructured data?

Discuss your familiarity with best practices in data management, such as ensuring proper data modeling for structured data and utilizing techniques like schema-on-read for unstructured data. Provide examples where applicable.

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To encourage understanding and follow-through across every medical conversation.

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Full-time, hybrid
DATE POSTED
December 15, 2024

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