Business Intelligence Engineer

Remote, Anywhere in the US

As our Business Intelligence Engineer, you are the ultimate architect of our data and the bridge to our AI-driven future. You’ll clear out the noise to create a single, trusted source of truth that powers critical business decisions and fuels our homegrown AI tools. By building a rock-solid data foundation, you ensure our internal teams, external partners, and digital systems always have accurate, reliable insights. Ultimately, your work empowers us to scale our platform and deliver life-changing autism therapy to families nationwide.

• W2 Employee

• 100% Remote

• 4+ years of experience in data engineering, analytics engineering, or BI architecture

• Deep SQL proficiency — you write complex queries fluently and think in terms of data models, not just ad hoc queries

• Strong experience with dbt: building models, writing tests, managing the DAG, and thinking in dimensions and facts

• Hands-on Amazon QuickSight experience — or deep experience with a comparable BI platform and a demonstrated ability to learn new tooling quickly

• You think like a data modeler: you consider how a design decision today affects the flexibility and trustworthiness of reports built on top of it tomorrow

• Familiarity with LLM-assisted BI tools, AI-native data products, or QuickSight AI features — you're not afraid of this space and ideally excited by it

• Strong communication skills: you can explain a data model decision to a non-technical stakeholder without making them feel lost

• Ability to work closely with business stakeholders to understand domain context — you can't model data well if you don't understand what the data means

Nice to have:

• Experience with clinical data, healthcare outcomes metrics, or payor reporting

• Familiarity with RAG pipelines, vector databases, or AI inference infrastructure — awareness of how BI data feeds AI systems

• Background in a high-compliance data environment (HIPAA, SOC 2)

• Experience migrating from one BI platform to another (Mode, Looker, Tableau, or similar)

Data Modeling & Semantic Layer

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  Design and maintain dbt models that encode business logic, metric definitions, and dimensional structures — the foundation that all BI reports are built on

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  Enforce consistent metric definitions across the semantic layer so that every downstream report reflects the same agreed-upon numbers

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  Work closely with the Senior Manager of Data to translate the definitions alignment work into concrete dbt model implementations

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  Document data models clearly enough that analysts and business stakeholders can understand what each model contains and how to use it

QuickSight Architecture & Administration

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  Own the AnswersNow QuickSight environment end-to-end: data source connections, SPICE datasets, refresh schedules, access controls, and performance

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  Architect the QuickSight layer for the five-domain dashboard buildout — designing for maintainability, performance, and consistent user experience

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  Lead the technical execution of the Mode-to-QuickSight migration, working with the Senior Manager of Data on sequencing and stakeholder communication

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  Configure and leverage QuickSight AI features (QuickSight Q, AI-assisted narratives) to extend the value of dashboards beyond static charts

Proprietary Agent Quality

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  Own the data quality and model accuracy that the our homegrown analytics agent depends on — if the agent gives a wrong answer, the root cause often lives in the data layer

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  Build validation checks, data quality tests, and monitoring that surface issues before they reach the agent or downstream users

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  Partner with the Data Science team on where the BI layer intersects with AI inference pipelines

Payor Outcomes Reporting

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  Design and maintain outcomes reporting packages for external payor audiences, including clinical outcome metrics, utilization summaries, and quality indicators

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  Ensure payor-facing reports meet accuracy standards — these reports carry external contractual and reputational weight

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  Work with clinical and business stakeholders to define the metrics and formats that payor partners require

AI-Native BI

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  Stay current on LLM-assisted BI tools and evaluate where they can reduce the burden of report creation, metric explanation, or ad hoc analysis

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  Apply AI-native thinking to BI infrastructure — designing datasets and models that are well-suited to be queried by both humans and AI agents

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  Contribute to the team's understanding of where AI can accelerate BI delivery and where human judgment is irreplaceable

AnswersNow welcomes applicants of all backgrounds, experiences, and abilities. We believe a diverse team is a strong team, and are committed to provide a fair and equitable experience for every candidate. If you require reasonable accommodations at any stage, we encourage you to reach out. We’re here to support!

Learn more about us at getanswersnow.com.

E-Verify & Right to Work
AnswersNow participates in E-Verify and electronically verifies the work authorization of all new hires upon employment. E-Verify is only used after a job offer has been accepted; it is not used to pre-screen applicants.

For more information, view the E-Verify Participation and Right to Work posters in English and Spanish.