Jobs at H1

Lead and scale an enterprise pharma sales organization to drive new logo acquisition, renewals, and expansion. Recruit and develop AEs and AMs, build repeatable sales and renewal processes, partner with Marketing, Customer Success, Product, and RevOps, provide executive deal support, and represent the company externally to grow revenue and retention across life sciences accounts.

As a Staff Data Engineer on the Data Lake team, you will architect, build, and scale distributed ETL pipelines, ensuring data quality and leading the engineering team. You will also drive large-scale data processing and technical initiative leadership.

Build and maintain scalable data ingestion and enrichment pipelines integrating diverse sources (CSV, Parquet, JSON, APIs). Ensure data quality and validation, transform/enrich datasets, integrate with core platforms, participate in code reviews, testing, deployment, and monitoring, and collaborate with cross-functional stakeholders to deliver reliable, performant data solutions.

Lead design and development of the H1 Knowledge Graph and Search platform. Own feature lifecycle, evolve search/graph systems, optimize performance and scalability, maintain data pipelines, ensure data quality and security, mentor engineers, and drive architecture and integration patterns.

The Staff Data Engineer will lead the architecture and scalability of H1's healthcare data processing systems, ensuring efficient entity resolution and big data operations. Responsibilities include design and optimization of distributed Spark pipelines, team leadership, and collaboration with AI/ML teams to enhance data processing capabilities.

Lead end-to-end evaluation, scoping, and onboarding of new healthcare data sources. Define field mappings, acceptance criteria, ingestion and entity-resolution rules, perform QA and anomaly detection, translate client requirements into integration specs, and produce maintainable documentation before handing off to maintenance teams.

Lead architecture and implementation of scalable backend services and distributed data platforms for large healthcare datasets. Drive technical roadmap, build high-throughput processing systems and APIs, collaborate with product and ML teams, mentor engineers, and own production deployments and reliability for mission-critical data capabilities.

As a Senior Engineer on the Digital Health team, you will design, build, and maintain APIs and services for the Find Care platform while ensuring performance, security, and compliance.

Lead day-to-day product delivery for PDE by embedding with engineering and product teams, running Scrum of Scrums, tracking dependencies, configuring and owning Jira, establishing sprint cadences and delivery artifacts, coaching teams on scrum best practices, and driving cross-team coordination to ensure P0 initiatives ship on time.

As a Staff Data Engineer, lead significant data projects, ensuring scalable architectures and optimized data pipelines, while mentoring others and collaborating cross-functionally.

The AI Scientist will design and implement machine learning models for clinical data platforms, collaborating with engineers and MLOps teams to optimize insights from healthcare datasets and integrate models into production systems.

Develop and maintain full stack web applications, building APIs, user interfaces, and ensuring efficient data flow in a clinical data platform environment.

Own enterprise client implementations from intake to sign-off: gather and document requirements, coordinate engineering/design/data delivery, run client relationships, manage scope and timelines, validate front-end and data deliverables, track projects in Jira/Linear, and improve implementation repeatability with a path toward product ownership.

Lead enterprise implementations for healthcare and life sciences customers, translating business requirements into scalable platform solutions, managing integrations (APIs, AWS/S3, Snowflake, Databricks, SFTP/FTPS), configuring Salesforce, troubleshooting production issues, validating data quality, running client workshops, and coordinating cross-functional teams to deliver timely, enterprise-grade SaaS deployments and post-launch support.