Remote Position
[Remote] Staff Data Engineer
🌍 Remote · United States
💼 Full-time
Note: The job is a remote job and is open to candidates in USA. Clarium is a healthcare technology company developing an AI-powered platform to improve hospital supply chain operations. The Staff Data Engineer will set technical direction for the data platform, architect AWS-based infrastructure, build reliable pipelines, model supply chain data, and establish standards for data quality and governance. The role also partners with cross-functional teams and mentors engineers.
Responsibilities
- 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 the observability to back them up
- Model supply chain data from external ERP systems into a coherent, reusable warehouse model, and lead the migration of legacy assets toward it
- Tune performance and cost across Postgres and Snowflake, including query plans, indexing, partitioning, warehouse sizing, and storage strategy
- Establish engineering standards for data work (testing, code review, CI/CD, data quality checks, documentation) and mentor engineers through design reviews, pairing, and honest technical feedback
- Partner with analytics, product, and engineering teams to turn ambiguous questions into durable data models instead of ad hoc extracts
- Lead governance for sensitive data, including lineage, access controls, retention, auditability, and de-identification where required
Skills
- 8+ years of data or software engineering experience, including significant time owning systems end to end in production
- Expert-level SQL: you write complex analytical queries as a matter of course and can read a query plan and explain why something is slow
- 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
- Hands-on experience with data pipeline and orchestration tooling such as Airflow, Dagster, Prefect, dbt, Fivetran, Spark, or Kafka; we care more about depth and judgment than an exact stack match
- Production experience running data workloads on AWS (e.g., S3, RDS, Lambda, ECS), with an understanding of the cost, security, and networking implications of how you build
- A track record of leading multi-quarter, cross-team initiatives that depended on teams you don't manage, and comfort with the ambiguity of deciding what should be built
- Postgres and Snowflake strongly preferred
- 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, including where it tends to be unreliable
- Infrastructure-as-code and deployment automation (Terraform, CDK, CI/CD for data infrastructure)
- Streaming and event-driven architectures, or data quality and observability tooling
- Need to Know: SQL · Python · Postgres · Snowflake · AWS (S3, RDS, Lambda, ECS)
- Nice to Know: Terraform · Github Actions · EKS / Kubernetes · dbt · Prefect · Apache Kafka
Benefits
- Incentive Stock Options proportionate to your salary
- Fully remote, with a NYC co-working space available; distributed team across multiple time zones with opportunities for in-person time
- Unlimited PTO
- Top-tier health, vision, and dental benefits
- 401K
- The opportunity to build on a strong foundational team with deep data and engineering roots at a stage where your work genuinely shapes the product
- A fast-paced, high-growth environment where we move quickly to solve critical healthcare challenges
- The chance to empower frontline healthcare workers by automating the administrative friction in their day-to-day
- Collaborative work alongside a high-caliber team of clinicians, engineers, and revenue leaders
Company Overview
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