Staff Data Engineer

March 17

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H1

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H1 is a global healthcare intelligence company that connects life sciences, payors, providers, and patients to AI-enabled data analytics and groundbreaking research to advance medicine. It provides enterprise solutions like HCP Universe, Trial Landscape, and Precise, helping healthcare professionals to access accurate and comprehensive data for clinical trials, scientific research, and medical affairs. H1 empowers medical missions and humanitarian work through H1 Connect and enhances diversity and inclusion in clinical trials by providing insights to improve patient diversity and site performance. The company plays a key role in enabling access to healthcare information and evidence-based medicine globally.

healthcare • provider data • healthcare professional information • diversity data • medical affairs

201 - 500 employees

⚕️ Healthcare Insurance

🤖 Artificial Intelligence

🧬 Biotechnology

📋 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 a Staff Data Engineer on the H1DN Team, you will be a hands-on technical leader, directly contributing to the development of scalable and efficient data architectures. You will collaborate closely with two IC team members, guiding them while actively participating in the work. This role centers on data ingestion and enrichment workflows, ensuring seamless integration of client data from various sources (CSV, Parquet, JSON, APIs) and addressing scalability, data quality, and standardization challenges. • You will: - Lead the development of new features within our client data ingestion platform, transforming, standardizing, and enriching with H1 dataset to meet business needs, including customizable solutions for high-stakes client integrations. - Focus on optimizing infrastructure to deliver product- and client-ready insights efficiently, ensuring enriched data integrates seamlessly into broader pipelines. - Collaborate with clients, subject matter experts, and product teams to drive critical integrations and shape the evolution of data workflows. - Establish best practices for data quality, system reliability, and scalable processing to support growing datasets. - Mentor and guide engineers on the team, promoting best practices and fostering a culture of technical excellence. - Advocate for engineering improvements, including scalable designs, quality assurance, and technical documentation standards. - Serve as a cultural leader within the engineering team, promoting high standards of excellence and continuous improvement in engineering practices. - Ensure the projects you work on deliver clear end-user impact, align with strategic goals, and are accountable for meaningful outcomes.

🎯 Requirements

• 8+ years of experience in data engineering, specializing in building scalable data pipelines and enrichment processes, with a strong track record of working with large datasets, including ingestion, transformation, and optimization • Proficiency in Spark, Python, and SQL for building scalable data processing pipelines. • Hands-on experience with Kubernetes for container orchestration and deployment. • Strong background in AWS, including services such as S3, Lambda, ECS, and RDS for data infrastructure. • Strong SQL skills, including the ability to write optimized complex queries for large datasets using advanced SQL operators such as GROUP BY, HAVING, window functions, and complex joins. • Experience with EMR and Databricks to optimize large-scale data workflows. • In-depth understanding of optimizing LLM usage in production, with experience integrating LLMs into real-world applications and applying LLM-powered insights within data pipelines or customer-facing solutions

🏖️ Benefits

• 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