Note: The job is a remote job and is open to candidates in USA. Medbridge is a software company developing technology solutions for healthcare providers to improve patient outcomes and reduce the cost of care. The Staff Data Engineer will own the architecture, security, reliability, and data movement of the Snowflake-centered data platform while building reliable pipelines, governance, and data delivery capabilities for analytics, AI/ML, applications, and customer-facing products. The role leads cross-functional technical initiatives and influences engineering standards without direct people management.
Responsibilities
- Own the target-state architecture and technical roadmap for Medbridge’s Snowflake-centered data platform, balancing security, reliability, usability, innovation, cost, and operational complexity
- Build and operate reliable data pipelines and integrations using strong Python and SQL engineering practices, covering ingestion, incremental processing, schema evolution, failure handling, retries, reconciliation, observability, and recovery across key operational and SaaS data sources
- Design and enforce Snowflake security and RBAC, applying least privilege, separation of duties, auditability, secure sharing, retention, monitoring, and appropriate access patterns for internal users, external use cases, service accounts, and AI workloads
- Establish production-grade engineering and platform operations, including testing, version control, code review, CI/CD, secrets management, environment promotion, deployment and rollback, service expectations, monitoring, alerting, incident response, and recovery
- Own data governance, contracts, and technical lineage, maintaining source-system ownership and inventory while establishing data contracts, schemas, interfaces, quality expectations, change management, deprecations, migrations, documentation, and clear communication of downstream impact
- Enable secure and reliable data delivery and consumption, creating reusable patterns and interfaces that move data from Snowflake into applications, APIs, analytics, ML/AI workloads, and customer-facing products while making data easier to discover, understand, access, and trust
- Lead cross-functional technical initiatives and raise engineering standards, partnering with Analytics Engineering, DevOps, Data Science, Security, Product Engineering, ML, and Integrations to establish pragmatic patterns, enable AI/ML workloads, evaluate build-versus-buy decisions, and continuously reduce unnecessary platform complexity
Skills
- Deep experience designing and operating cloud data platforms, including ingestion, orchestration, warehouse architecture, security, reliability, and production operations in regulated environments; healthcare experience is a plus, not a requirement
- Strong Snowflake expertise, including RBAC, contractual data separation, secure internal and external access patterns, secure views and sharing, warehouse and resource management, query and cost optimization, metadata, monitoring, and environment design
- Proven data pipeline expertise, building and operating batch and incremental pipelines with explicit failure handling, retries, reconciliation, observability, recovery, and clear ownership
- Strong Python and SQL engineering skills, with experience in modular design, testing, version control, code review, packaging, CI/CD, and maintainable interfaces
- Experience operating production data systems, including development, staging, and production workflows, deployment practices, and effective partnership with DevOps or platform engineering
- Experience delivering data beyond the warehouse, including applications, APIs, ML systems, reverse-ETL, or other operational consumers, with strong data contracts covering ownership, quality, compatibility, schema evolution, deprecation, and breaking-change communication
- Sound security and architectural judgment, including experience partnering with Security, Privacy, or Legal on sensitive or regulated data and making pragmatic build-versus-buy and managed-service decisions
- Strong technical communication and cross-functional leadership, with the ability to explain architecture, risks, incidents, and tradeoffs clearly; lead complex initiatives; establish standards; and influence without formal authority
- A self-directed, low-ego approach to engineering, favoring simple, supportable solutions, shared understanding, and a strong developer and data-consumer experience over unnecessary complexity
- A technical or quantitative degree, or equivalent capability demonstrated through professional experience
- Advanced Snowflake security experience, including secure access for employees, external customers or partners, and AI or service workloads
- Experience building data-to-product capabilities, including warehouse-to-product or reverse-data flows and collaboration with application engineers on customer-facing data products
- Experience enabling ML/AI workloads in Snowflake, including Snowpark, Model Registry, ML Jobs, compute pools, containerized workloads, or comparable managed capabilities
- Experience modernizing developing data environments, with exposure to Openflow, dbt, Terraform, data catalogs, observability platforms, or healthcare interoperability/EHR/EMR ecosystems, while introducing operational rigor without over-engineering
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