Staff Software Engineer, Data

IntusCare provides an end-to-end healthcare technology ecosystem for Programs of All-Inclusive Care for the Elderly (PACE), supporting care coordination, risk adjustment, population health, and utilization management. The Staff Software Engineer, Data will guide the technical direction of the ELT platform, lead complex architecture and reliability initiatives, mentor engineers, and establish standards for code quality, security, observability, and HIPAA-compliant handling of protected health information.

Responsibilities:

• Help drive the technical direction of the ELT platform on a multi-quarter horizon, balancing strategic investments against pragmatic delivery
• Write the design documents that anchor major initiatives, and set the standard for how the team writes and reviews design work
• Break down large, ambiguous initiatives into work that senior engineers can lead and lower-level engineers can execute
• Partner with product, leadership, and cross-functional engineering teams to translate business goals into platform strategy
• Provide architectural guidance across the codebase, and make the calls on tradeoffs that span multiple projects
• Anticipate systemic risks, scaling constraints, and reliability failure modes before they surface, and shape the roadmap to address them
• Provide the deepest, most substantive feedback on pull requests and design documents. Your reviews reshape approaches, not just implementations
• Mentor and coach senior engineers, and set the growth path for engineers at every level of the team
• Set the bar for code quality, testing, observability, security, and HIPAA-compliant handling of PHI, and hold the team to it
• Lead the response for the most complex incidents, and drive the follow-up work that prevents them from recurring
• Use Claude Code and other AI-assisted tooling as a force multiplier, define the team’s practices around AI use, and shape how the team’s workflow evolves as tooling matures

Requirements:

• · 7+ years of professional software or data engineering experience, with a track record of technical leadership at increasing scope
• · Deep expertise in SQL and Python
• · Deep hands-on expertise with Airflow or a comparable orchestrator, dbt or another modern transformation framework, and Snowflake, BigQuery, Redshift, or a comparable cloud data warehouse
• · Experience resolving problems of scale at the warehouse, data, and infrastructure levels
• · Extensive experience in at least one adjacent domain such as data platform architecture, HIPAA-compliant data handling, or reliability engineering
• · Proven ability to see around corners: you anticipate the design flaws, edge cases, scaling issues, and organizational risks that other engineers do not notice until much later, and you raise them in time to shape the outcome
• · Track record of owning a technical roadmap, translating business goals and product requirements into shippable design documents, and shepherding the work through multiple engineers to delivery
• · Track record of mentoring engineers
• · Comfort operating across the stack: application boundaries, infrastructure, deployment tooling, observability, and incident response
• · Strong judgment on when and how to use AI-assisted development, and the ability to set team-wide practices around it
• · A quality-driven mindset that materializes as an emphasis on testing rigor
• · Excellent written and verbal communication. You produce documents that align engineers, product, and leadership on the same page
• · A pragmatic disposition: you know when to invest in the long term, when to pay down debt, and when to ship the imperfect thing
• Work location: This is a fully remote role based in the United States
• Sponsorship: This position is not eligible for sponsorship
• · Prior experience as a staff or principal engineer on a data platform team
• · Experience with healthcare data standards (HL7, FHIR) or EHR integrations
• · Experience with value-based care, PACE, or Medicare/Medicaid populations
• · Snowflake certifications (SnowPro Core, Architect)
• · Experience running services on Kubernetes and setting production reliability standards
• · Experience with MongoDB or another document database
• · Deep experience with monitoring and observability tooling (Grafana, Loki, Prometheus, or similar)
• · Experience shaping data engineering hiring, leveling, and organizational design
• · Familiarity with machine learning or AI applications in healthcare analytics