Data Engineer; Emerald

• As a Staff Data Engineer on the Emerald team, you will play a critical role in shaping the architecture, scalability, and technical direction of H1’s healthcare entity resolution platform. EMERALD is responsible for linking large-scale external healthcare datasets, including Pub Med, clinical trials, conferences, ct.gov, and web-collected data to H1’s canonical physician and organization profiles
• This role sits at the intersection of distributed data engineering, entity matching, identity resolution, and large-scale healthcare data processing. You will lead a small team of engineers while remaining deeply hands‑on technically, owning the systems and pipelines powering automatching, grouping logic, identity mapping, deduplication, and enrichment workflows processing tens of millions of records
• You will partner closely with Product, AI/ML, Analytics, and Engineering teams to improve platform accuracy, scalability, reliability, and operational efficiency across one of H1’s most critical data platforms
• Lead the design, optimization, and scalability of distributed Spark/PySpark pipelines powering entity resolution and large-scale healthcare data processing
• Own systems supporting automatching, identity mapping, grouping logic, deduplication, enrichment, and auto‑approval workflows across healthcare provider and organization datasets
• Build and maintain scalable processing frameworks for Pub Med, clinical trial, ct.gov, conference, and other healthcare data sources
• Drive infrastructure optimization initiatives focused on improving throughput, runtime, observability, and cloud compute cost efficiency
• Partner closely with AI/ML teams to integrate matching and resolution models into EMERALD and improve matching precision and recall
• Lead complex technical initiatives from architecture and design through deployment, monitoring, and long‑term production support
• Serve as a technical leader and mentor across the team through code reviews, technical guidance, and engineering best practices
• Collaborate directly with Product and business stakeholders to align technical solutions with operational and customer needs
• Support production operations, incident response, troubleshooting, and ongoing platform reliability

• 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

Experience building scalable ETL/ELT frameworks across both batch and streaming architectures

Extensive experience with Apache Spark and AWS-based big data technologies including EMR, S3, and distributed compute environments

Experience optimizing large-scale Spark workloads for performance, scalability, and infrastructure cost efficiency

Experience with containerization and infrastructure technologies such as Docker, Kubernetes, and Terraform Experience working with relational or distributed databases such as PostgreSQL or Redshift You bring strong hands‑on engineering expertise across distributed computing, large‑scale data processing, and infrastructure optimization while also helping guide technical direction and mentor engineers across the organization

Strong grasp of software engineering fundamentals including distributed systems, data structures, concurrency, and system design

Experience working with healthcare, life sciences, Real World Evidence (RWE), or large‑scale healthcare datasets is strongly preferred

Strong coding experience in Python (PySpark), Scala, Java, or equivalent languages used for distributed processing systems

Deep expertise with distributed data processing frameworks such as Apache Spark and Hadoop, particularly within AWS environments

Strong communication and collaboration skills across both…