Big Data Engineer

at H1
  • $150k-$175k
  • Remote - United States

Remote

Data

Mid-level

Job description

At H1, we believe access to the best healthcare information is a basic human right. Our mission is to provide a platform that can optimally inform every doctor interaction globally. This promotes health equity and builds needed trust in healthcare systems. To accomplish this our teams harness the power of data and AI-technology to unlock groundbreaking medical insights and convert those insights into action that result in optimal patient outcomes and accelerates an equitable and inclusive drug development lifecycle.  Visit h1.co to learn more about us.

Data Engineering is responsible for the development and delivery of our most important asset - our data. Looking across thousands of data sources from across the globe, the data engineering team is responsible for making sense out of that data to create the world’s most extensive and comprehensive knowledge base of healthcare stakeholders and the ecosystem they influence. It is our job to ensure that only accurate, normalized data flows through to our customers, and at a velocity that keeps up with the changes in the real world. As we rapidly expand the markets we serve and the breadth and depth of data we want to collect for our customers, the team must grow and scale to meet that demand.

WHAT YOU’LL DO AT H1

As a Staff Data Engineer, you will be the most senior individual contributor as well thought leader working mostly independently on a RWE team. You will play a critical role as a technical expert working as an IC, shaping the technical strategy and architecture of our internal Real World Evidence product. You will have direct founder-level interactions. This position requires a high degree of independence and the ability to navigate and resolve complex technical challenges and dependencies with minimal oversight. Your work will focus on high-priority projects that deliver significant end-user impact, and you will mentor other engineers to achieve their objectives and enhance their technical capabilities. You will also be instrumental in advocating for and implementing best practices and technical excellence across the team.

You will:

- Lead and own some of the key datasets in the RWE team, shaping the strategy and architecture to ensure the smooth development, deployment, and scalability of data pipelines  across the tech stack, while aligning with organizational goals.

- influence data product for  the dataset you are responsible for  by engaging with SME and becoming yourself SME for the domain

- work with 100s of TB data by implementing cost efficient data pipelines.

- Drive your team’s success by providing guidance, removing obstacles creatively, and shaping roadmaps and objectives that support consistent progress.

- Tackle ambiguous and complex technical challenges independently, with minimal need for external support.

- Develop a deep understanding of end-user needs and collaborate cross-functionally to deliver high-impact solutions.

- Focus on high-priority projects (P0s and P1s) that create significant value for users and stakeholders.

- Mentor and support engineers on your team, helping them grow technically and achieve their goals.

- Champion a culture of engineering excellence by promoting best practices, high standards, and continuous improvement.

- Ensure your projects deliver meaningful, measurable outcomes that align with strategic objectives and end-user impact.

ABOUT YOU

You’re a hands-on, visionary data engineering thought leader IC with a strong track record of building scalable systems and pipelines. You work independently, work  through complex challenges, and align technical efforts with broader strategic goals. You’re collaborative, proactive, and committed to engineering excellence.

- Skilled in solving complex data problems and delivering innovative solutions.

- Experienced in cross-functional collaboration and strategic alignment.

- Clear communicator with strong technical documentation skills.

- Committed to data quality, security, and best engineering practices.

- Self-driven, with a focus on ownership and risk mitigation.

- Passionate about mentoring and building high-performing teams.

REQUIREMENTS

- 8+ years in data engineering with a track record of building and maintaining scalable data systems and pipelines.

- 5+ years working with big data tools such as Apache Spark, Hadoop, particularly on AWS EMR, with practical hands-on experience in tools like Apache Spark, and Hudi/Delta Lake.

- Experience with databases like PostgreSQL

- Software management tools such as Git, JIRA, and CircleCI

- Developer Operations, deploying to systems like AWS EMR, and Kubernetes

COMPENSATION

This rolepays $150,000 to $175,000 per year, based on experience, in addition to stock options.

Anticipated role close date: 06/28/2025

H1 OFFERS

- Full suite of health insurance options, in addition to generous paid time off

- Pre-planned company-wide wellness holidays

- Retirement options

- Health & charitable donation stipends

- Impactful Business Resource Groups

- Flexible work hours & the opportunity to work from anywhere

- The opportunity to work with leading biotech and life sciences companies in an innovative industry with a mission to improve healthcare around the globe

H1 is proud to be an equal opportunity employer that celebrates diversity and is committed to creating an inclusive workplace with equal opportunity for all applicants and teammates. Our goal is to recruit the most talented people from a diverse candidate pool regardless of race, color, ancestry, national origin, religion, disability, sex (including pregnancy), age, gender, gender identity, sexual orientation, marital status, veteran status, or any other characteristic protected by law.

H1 is committed to working with and providing access and reasonable accommodation to applicants with mental and/or physical disabilities. If you require an accommodation, please reach out to your recruiter once you’ve begun the interview process. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

#H1-HF

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