Skypoint is a HITRUST r2–certified Agentic AI platform for healthcare operations, designed to accelerate productivity and operational efficiency across healthcare organizations. Our platform enables healthcare providers, payers, and senior care organizations to unify fragmented data, model industry-specific ontologies, and deploy AI agents that automate workflows and support better, faster decision-making.

Founded in 2020 in Portland, Oregon, Skypoint has grown to a team of over 75 employees and now serves more than 100 customers. We are proud to be recognized on Deloitte’s 2024 and 2025 Technology Fast 500™, celebrating the fastest-growing technology companies in North America, and to be featured on the INC. 5000 list in 2025, reflecting our strong and sustained revenue growth over the past three years.

About the Role

We are looking for a Forward-Deployed Analytics Engineer who knows the senior living world from the inside — and who is energized by bringing the power of modern data and AI to an industry that is ready for it. This is a hands-on implementation and customization role, embedded within our customer-facing delivery team, working directly with senior living operators, CCRCs, assisted living communities, skilled nursing facilities, and long-term care organizations to deploy, configure, and tailor our data and analytics platform to their specific operational needs.

You are someone who understands what matters to a senior living operator: census and occupancy, move-in/move-out trends, care acuity, labor costs, resident satisfaction, and the relentless pressure to do more with less. You know how these organizations are structured, how their data is generated, and what a great report or dashboard actually looks like to a Director of Operations, a CFO, or a Regional VP.

On the technical side, you are a Power BI and Microsoft Fabric practitioner who is as comfortable configuring and customizing standardized models as you are building from scratch. Much of your work will center on deploying and tailoring our pre-built semantic models and report templates to fit each client's operational structure — understanding what to adjust, what to leave alone, and how to extend the standard in ways that are clean and maintainable. You do all of this with an AI-first approach, using the latest tools to work faster and more creatively. You get genuine satisfaction from seeing a customer go live, watching their team light up when they pull their own data for the first time, and knowing you built something they will rely on every day.

What You'll Do

Product Implementation & Customer Onboarding

    Lead the technical implementation of our analytics platform for senior living clients — from initial data connectivity and source mapping through to go-live and handoff

    Configure and customize dashboards, reports, and data models to reflect each client's operational structure, KPIs, and workflows

    Work directly with client stakeholders — operations, finance, clinical, and IT teams — to understand their data landscape, validate requirements, and align on deliverables

    Manage multiple concurrent implementations with clear communication, organized workplans, and a bias toward getting customers to value quickly

    Serve as the primary technical point of contact for clients during implementation, building trust through responsiveness, expertise, and follow-through

Model Implementation, Configuration & Customization

    Deploy and configure our standardized Power BI semantic models and report templates for each client — mapping source data to standard fields, validating outputs, and ensuring models reflect the client's operational structure accurately

    Customize standard models thoughtfully and sustainably — extending them to accommodate client-specific KPIs, care settings, or organizational hierarchies without undermining the integrity of the standard layer

    Develop DAX measures and calculated fields where customization is needed, accurately representing senior living metrics: occupancy rate, average length of stay, payer mix, labor hours per resident day, care acuity trends, and more

    Recognize when a client need is best met by configuring the standard versus building something custom — and communicate that distinction clearly to clients and internal teams

    Ensure deployed models are AI-ready: structured for Copilot, optimized for natural language Q&A, and documented so both human analysts and AI tools can navigate them effectively

Reporting & Dashboard Delivery

    Build polished, intuitive Power BI reports and dashboards tailored to senior living audiences — from frontline supervisors to C-suite executives

    Translate operational concepts (census management, staffing ratios, skilled mix, therapy minutes, fall rates, re-hospitalization) into clear, actionable visualizations

    Implement row-level security, role-based access, and workspace governance appropriate to multi-community and multi-region operators

    Create report templates and standardized assets that can be reused and adapted efficiently across similar client implementations

AI-First Engineering & Tooling

    Use AI-assisted coding and development tools (Microsoft Copilot, GitHub Copilot, Cursor, or equivalent) as a core part of your daily workflow — to write DAX faster, generate documentation, draft data models, and accelerate every phase of implementation

    Design semantic models that are optimized for AI consumption — structured to support Copilot for Power BI, natural language queries, and agentic workflows that surface insights automatically

    Explore and apply AI-powered features within Microsoft Fabric and Power BI to deliver smarter, more automated analytics experiences for clients

    Bring an AI-first perspective to implementation work: always asking where automation, intelligence, or AI assistance can improve the quality or speed of what you are delivering

Project Management & Client Communication

    Basic project management - maintain workplans, tracking open items, managing dependencies, and keeping stakeholders aligned from kickoff through go-live

    Communicate proactively with clients — surface risks early, set realistic expectations, and translate technical blockers into plain-language updates that non-technical stakeholders can act on

    Manage scope with confidence: know how to have productive conversations when requirements shift, timelines are at risk, or a client request falls outside agreed scope

    Produce clear project artifacts — kickoff decks, implementation trackers, status reports, and handoff documentation — that keep clients informed and internal teams aligned

Collaboration & Continuous Improvement

    Partner with product and engineering teams to provide field feedback on platform capabilities, common customization needs, and gaps observed during client implementations

    Contribute to a growing library of implementation accelerators, model templates, and best practices that reduce time-to-value for new clients

    Participate in internal knowledge sharing, helping teammates build fluency in senior living domain concepts and implementation patterns

What You Bring

Senior Living & Long-Term Care Domain Expertise

    4+ years of experience working with or within senior living, long-term care, or post-acute care organizations — as an operator, analyst, implementation consultant, or technology specialist

    Strong familiarity with senior living operational concepts: independent living, assisted living, memory care, CCRC/life plan communities, skilled nursing, and the distinct data and reporting needs of each care setting

    Familiarity with common senior living technology platforms and data sources: EHR/EHR-adjacent systems (PointClickCare, MatrixCare, American HealthTech), CRM tools (Salesforce, Enquire, Welbi), financial systems, and occupancy management platforms

    Understanding of the KPIs and reporting frameworks that matter to senior living operators: census and occupancy, NOI, labor cost per occupied unit, skilled mix, elopement/incident reporting, and resident satisfaction metrics

    Experience with CCRC or skilled nursing facility (SNF) environments is a meaningful plus — including an understanding of Medicare/Medicaid billing, MDS/RAI data, quality metrics (QM), Five Star ratings, and PDPM

Power BI & Microsoft Fabric

    Strong, hands-on Power BI skills — including semantic model configuration, DAX authorship, report design, deployment pipelines, and workspace administration

    Solid understanding of semantic model design principles: star schemas, fact and dimension relationships, calculated columns versus measures, and model performance management — applied primarily in the context of configuring and extending standardized models rather than building greenfield

    Comfortable working within an existing model framework: you can read a model someone else built, understand its logic, extend it cleanly, and know which customizations are safe versus which will create downstream problems

    Familiarity with Microsoft Fabric — including Lakehouses, Dataflows Gen2, Fabric Notebooks, OneLake, and Fabric pipelines for data integration and transformation

    Familiarity with Power BI Copilot and AI-powered features within the Fabric ecosystem, including how to structure data models to maximize AI utility

    Experience implementing Power BI in organizational settings: row-level security, deployment pipelines, tenant settings, sensitivity labels, and workspace governance

AI-First Mindset & Tooling

    You use AI tools every day — not occasionally. GitHub Copilot, Microsoft Copilot, Cursor, or similar tools are part of how you work, not something you are still evaluating

    You think about AI consumption when you design data models — structuring semantic layers so that Copilot, natural language Q&A, and future agentic workflows can navigate them without friction

    You are genuinely excited about what AI means for analytics in senior living — from automated anomaly detection in census data to AI-generated narratives in board reports — and you want to help clients get there

Data Fundamentals

    Solid understanding of data modeling concepts — star schema, dimensional modeling, fact and dimension tables — even if your primary tool is Power BI rather than a dedicated transformation layer

    Comfortable working with data in Excel, SQL (basic to intermediate), or other querying tools to explore, validate, and troubleshoot data during implementation

    Experience connecting Power BI or Fabric to a variety of source systems and data formats common in senior living environments

Nice to Have

    SQL, dbt, Databricks, or Snowflake experience — useful for deeper data pipeline work and enterprise-scale implementations, but not required

    Experience with Azure cloud services (Azure Data Factory, Azure Synapse) that underpin Microsoft Fabric

    Background in healthcare analytics more broadly — payer, provider, or health system experience that complements the senior living focus

    Familiarity with MDS/RAI data, PDPM, Five Star Quality Rating methodology, or Value-Based Purchasing programs for skilled nursing

    Experience with interoperability standards (HL7, FHIR) and API-based integrations with senior living EHR platforms

    Microsoft Power BI (PL-300) or Fabric (DP-600) certifications

Why This Role

    Work with an industry that genuinely needs what you bring — senior living operators are hungry for better data, and you will be one of the people who delivers it

    See the direct impact of your work: clients go from spreadsheets and gut instinct to real-time dashboards and AI-powered insights, and you get to watch it happen

    Build deep expertise at the intersection of senior living operations, modern data platforms, and AI — a rare and increasingly valuable combination

    Join a team where AI-first is a lived principle, not a talking point — you will be supported and expected to build with the best tools available

    Competitive compensation, comprehensive benefits, and a flexible remote-first culture with meaningful client interaction

Skypoint is an Equal Opportunity Employer. We do not discriminate based on race, color, religion, sex, national origin, age, disability, veteran status, or any other protected characteristic