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Salary: USD 170,000 - 210,000 / annual
Clarium is an AI-powered healthcare supply chain platform that helps hospitals optimize operations and reduce waste. The healthcare industry overspends on supply chain by over $25B annually due to fragmented data and inefficient workflows. Clarium's Astra OS platform provides end-to-end visibility and automation, trusted by leading health systems including Yale New Haven Health, Stanford, Geisinger, and Kaiser Permanente. Founded in 2020, the company has raised $43M in funding.
This is a staff-level individual contributor role focused on setting technical direction for the data platform rather than executing ticket-to-ticket work. You will decide how data is modeled, moved, and trusted across Clarium, leaving both systems and engineers measurably better.
Key responsibilities include:
- Own the architecture and technical roadmap for core data infrastructure on AWS, spanning ingestion, transformation, storage, and serving layers
- Design, build, and operate reliable batch and near-real-time pipelines with clear SLAs and observability
- Model supply chain data from external ERP systems into a coherent warehouse model and lead migration of legacy assets
- Tune performance and cost across Postgres and Snowflake, including query plans, indexing, partitioning, and storage strategy
- Establish engineering standards for data work (testing, code review, CI/CD, data quality checks, documentation) and mentor engineers through design reviews and technical feedback
- Partner with analytics, product, and engineering teams to convert ambiguous questions into durable data models
- Lead governance for sensitive data, including lineage, access controls, retention, auditability, and de-identification
You'll work across transactional databases and analytical warehouses, owning the pipelines connecting them. Much of the work involves supply chain data from hospital ERP systems where schemas and semantics vary by source and are rarely well documented—a significant portion of the role is deciding what should be built, not just building it.
REQUIREMENTS:
- 8+ years of data or software engineering experience, including significant time owning systems end-to-end in production
- Expert-level SQL: complex analytical queries and ability to read query plans and explain performance issues
- Strong Python for production data work, including pipeline code, transformation logic, testing, and tooling
- Deep experience with relational databases, including schema design, normalization tradeoffs, transactions, and performance tuning (Postgres and Snowflake strongly preferred)
- Hands-on experience with data pipeline and orchestration tooling such as Airflow, Dagster, Prefect, dbt, Fivetran, Spark, or Kafka
- Production experience running data workloads on AWS (S3, RDS, Lambda, ECS) with understanding of cost, security, and networking implications
- Track record of leading multi-quarter, cross-team initiatives that depended on teams you don't manage, with comfort with ambiguity in deciding what should be built
NICE TO HAVE:
- Experience with healthcare data (claims, EHR/EMR, HL7 or FHIR, ICD-10, CPT) or working under HIPAA with PHI, de-identification, and audit requirements
- Familiarity with supply chain data from ERP systems such as Oracle, Workday, or Lawson
- Infrastructure-as-code and deployment automation (Terraform, CDK, CI/CD for data infrastructure)
- Streaming and event-driven architectures, or data quality and observability tooling
