Staff Data Engineer (Data Lake)

• As a Staff Data Engineer on the Data Lake team at H1, you will play a critical role in shaping the architecture, scalability, reliability, and long-term direction of our core data platform. This role is designed for a highly technical engineer who is excited to grow into an Engineering Manager track while remaining deeply hands-on technically
• The Data Lake is the foundation of H1’s platform, responsible for the validation, accuracy, standardization, and quality of the data powering every downstream product and team across the organization. You will help lead the evolution of this platform while supporting and mentoring a growing team of engineers
• Architect, build, and scale distributed ETL/ELT pipelines and large-scale ingestion frameworks across structured and unstructured healthcare datasets
• Lead the evolution of H1’s Data Lake architecture with a focus on scalability, observability, reliability, and cost optimization
• Own and improve data quality, validation, normalization, and standardization workflows across thousands of global data sources
• Design and optimize batch and near real-time data processing frameworks using cloud-native distributed systems
• Optimize distributed compute and storage systems, including Spark workloads, query performance, partitioning strategies, and infrastructure efficiency
• Drive improvements in monitoring, governance, operational excellence, and production reliability across the platform
• Troubleshoot complex production data and infrastructure issues across distributed systems
• Partner closely with Product, Infrastructure, Security, Compliance, and downstream engineering teams to support scalable and secure data delivery
• Mentor engineers through technical leadership, architecture reviews, and engineering best practices
• Help define technical roadmap priorities and contribute to long-term platform strategy and execution planning
• Support production operations, incident response, and platform health as part of overall ownership of the Data Lake ecosystem

Benefits

• Flexible work hours
• Commuter benefits
• Stock options
• Computer setup
• Work from home opportunities
• Health & life insurance
• Retirement options
• Unlimited PTO
• Flex Give & Flex Spend
• Impactful BRGs

• You are a highly technical data engineer who thrives in lean, high-ownership environments and enjoys solving complex distributed systems challenges. You are excited by the opportunity to influence technical direction, mentor engineers, and grow into broader engineering leadership responsibilities while remaining hands-on
• Strong proficiency in Python (PySpark), Java, Scala, or similar programming languages
• Experience using AI-assisted coding tools (e.g., GitHub Copilot, Claude Code) to accelerate development while maintaining quality is encouraged
• Experience with Docker, Kubernetes, and modern containerization technologies
• Experience designing and scaling modern cloud-native data lake architectures and large-scale ingestion frameworks
• You excel at building reliable, observable, and maintainable data systems supporting critical business and analytics workloads
• Deep experience with Apache Spark and cloud-native big data platforms, preferably within AWS environments (EMR, Glue, S3, Athena, Redshift, or similar)
• Experience with large-scale data cleaning, parsing, normalization, and validation workflows preferred
• Experience with orchestration and workflow management tools such as Argo, Airflow, or similar technologies
• You are energized by ownership, autonomy, and solving ambiguous technical challenges
• You have deep experience designing and scaling distributed data platforms and large-scale pipelines in cloud-native environments
• Exposure to ML/AI-driven data enrichment, parsing, or validation workflows is a plus
• You are comfortable leading technical initiatives and influencing architecture decisions across teams
• 8+ years of experience in data engineering, software engineering, or related fields with significant experience building and scaling distributed data platforms
• You have strong expertise in distributed processing, performance optimization, and modern data architecture patterns
• Strong understanding of distributed storage systems, partitioning strategies, and file formats such as Parquet, Avro, and ORC
• Demonstrated technical leadership experience with interest in or experience mentoring and leading engineers
• You communicate effectively with both technical and non-technical stakeholders
• Experience working with healthcare, life sciences, publication, or large-scale entity-resolution datasets preferred
• Experience implementing monitoring, observability, and data quality frameworks within production environments
• You enjoy mentoring engineers and helping raise the engineering bar across teams
• Advanced SQL expertise, including performance tuning and optimization across large datasets

• Anticipated role close date: 8/1/2026