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Remote, Oregon, United States
Remote only
About Intus Care:
IntusCare is the only end-to-end ecosystem built specifically to help Programs of All-Inclusive Care for the Elderly (PACE) programs deliver exceptional care, strengthen financial performance, and stay compliant. IntusCare replaces outdated technology and manual workarounds with purpose-built solutions for care coordination, risk adjustment, population health, and utilization management. We empower teams to take control of their operations and improve outcomes for dual-eligible seniors- some of the most socially vulnerable and clinically complex individuals in the US healthcare system.
We are the data engineering team at IntusCare. We own the ELT platform that powers our DataHub product and internal analytics, built on Airbyte for ingestion, Snowflake as our warehouse, dbt for transformation, and Airflow for orchestration.
As a Staff Software/Data Engineer, you own a stake in the technical direction of the platform. You take the fuzziest, highest-impact problems on the team’s plate and turn them into strategies, designs, and shipped solutions. You are a force multiplier: the team’s ceiling rises because of the standards you set, the designs you write, the engineers you mentor, and the constraints you remove for everyone else. You believe in data-engineering with a software-engineering mindset.
We are a remote-first company. Our team members work from wherever they are most productive, and we invest in the tools and rituals that keep a distributed engineering team connected. We are committed to building a diverse and inclusive team, and we believe our best work happens when happy employees provide different perspectives to shape outcomes. Above all, we are passionate about the impact our platform has on the populations our clients serve.
Our five core values guide how we work together:
· Take Ownership for Responsibilities & Outcomes. We measure what matters and hold ourselves accountable for the results, the culture, and the company we build together.
· Think with Data First. We prioritize data-informed decisions and stay focused on measurable impact.
· Be Passionate about Impact. Our work exists to create positive change in the markets and communities we serve.
· Take Strides toward Growth & Innovation. We stay curious, welcome new ideas, and value effort and attitude from everyone on the team.
· Be Supportive of Each Other. We create an environment where teammates and clients feel welcomed, elevated, and set up to succeed.
Under the Director of Data Engineering and in collaboration with the team’s data architect and rest of the team:
- 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
· 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
· 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
· The platform is more coherent, more reliable, and easier to build on because of the decisions you make and the standards you set
· The design documents you write become the canonical references other engineers reach for
· Senior engineers seek you out for hard architecture calls and hard people calls, and they grow faster because of the way you invest in them
· Leadership and product trust your input on the roadmap, and you are consulted on decisions that affect the whole engineering organization
· Incidents and reliability issues in your area of ownership trend down over time
· The team’s practices around AI-assisted development mature under your guidance
· Your work removes constraints for the whole team. The engineers around you can do bigger and better work because of the ground you have covered
· Orchestration: Airflow on Kubernetes
· Ingestion: Airbyte on Kubernetes
· Warehouse: Snowflake
· Databases: Postgres, MongoDB
· Transformation: dbt
· Languages: SQL, Python
· AI tooling: Claude Code
· Monitoring: Grafana, Loki, Prometheus, incident.io
Working with protected health information is core to this role. Every engineer on our team follows HIPAA-compliant data handling practices as part of every task. As a Staff engineer, you set the standard for how the team handles PHI and you hold the whole team, including senior engineers, to that standard.
Compensation:
The base salary range for this role is 180K-190K. We expect the ideal candidate to fall near the midpoint of this range, though final compensation will be determined based on experience, skills, and organizational needs.
Work location: This is a fully remote role based in the United States.
Sponsorship: This position is not eligible for sponsorship.
