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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Business Intelligence Engineer - **Company:** Imagine Pediatrics - **Location:** United States - **Experience:** Experienced - **Salary:** $115,000.0 - $145,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Big Data, Cloud Database, Code Review, Continuous Integration, Data Presentation, Database Queries, Decision Support Systems, DevOps, Automation of Marketing, Performance Tuning, SQL Databases, Tableau (Software), Snowflake, Data Analytics, Software Version Control - **Published:** September 26, 2026 - **Apply:** https://www.thejobnetwork.com/job/business-intelligence-engineer-509979753 ## About the Role * 3+ years of experience in business intelligence, data analytics, analytics engineering or related disciplines; strong experience in healthcare * 2+ years of experience with Tableau demonstrating advanced use of calculations, parameters, performance tuning and interactivity * Strong SQL skills and the ability to build analytic tools quickly to generate actionable insights from large-scale data in Snowflake or similar cloud data warehouses * Strong dbt for data modeling with an engineering-minded approach: building reusable models, standardizing metric definitions, and reducing duplicated logic rather than treating each dashboard as an isolated deliverable * Systems thinking; you naturally consider how a dashboard, metric, or model fits into the broader analytics ecosystem, and design for downstream dependencies and future reuse rather than solving only the request in front of you * Demonstrated use of modern engineering practices including version control, CI/CD, testing, and code reviews * Comfort owning a project end-to-end, from gathering requirements directly from stakeholders, prototyping and stakeholder validation through build, QA testing, and user testing * Proven ability to communicate findings effectively through data storytelling that connects insights with business goals and impact * Familiarity with semantic layer concepts, self-service analytics enablement, or AI-assisted analytics tooling is a strong plus * Familiarity with healthcare data sources (e.g., claims, EHR, health information exchange) is a strong plus ## Description Reporting to the Manager, Business Intelligence, the Business Intelligence Engineer is responsible for working cross-functionally with stakeholders across the organization (e.g. clinical, operational, product, finance, and beyond) to drive analyses and insights that lead to more informed decisions and improved business performance. This role owns the full business intelligence lifecycle: understanding a stakeholder's workflow, defining the metrics that monitor it, and delivering trusted, reusable analytical solutions from prototype through production. This role will be part of a fast-growing, fast-paced technology organization working to create bespoke solutions to support medically complex children on Medicaid, increasing safe days at home. You will: * Design, build, and maintain Tableau dashboards that are user-friendly, performant, meet production standards, and enable data-driven decision making across the organization * Design dbt models as reusable data products rather than one-off, dashboard-specific logic; check for and reuse existing models, metrics, and semantic definitions before building new ones, and own the consistency of what you introduce * Partner with stakeholders across organization to gather requirements, understand how their workflow operates, and translate that understanding into the metrics and key performance indicators needed to monitor it * Navigate ambiguous project requirements with limited information, recommend solutions and adapt to evolving business priorities and project types * Own the full business intelligence lifecycle end-to-end: prototyping and validating an approach with stakeholders, building the underlying data model and dashboard, QA testing for accuracy and edge cases, and user testing to confirm the solution meets stakeholders' expectations before it ships * Proactively flag metric or logic inconsistencies you encounter across domains, even ones outside your immediate project, rather than working around them * Use SQL and other tools to collect, process, and analyze large datasets from claims, EHR, HIE, and other programmatic and operational sources * Support self-service analytics by building dashboards and semantic layer components that stakeholders can confidently explore and extend on their own, reducing one-off reporting requests * Complete analytic ticket requests and ad-hoc reporting needs, communicating with stakeholders on status and relaying priorities * Partner with Analytics Engineering, Health Care Economics, Data Science on shared models, upstream data quality, and new tools and capabilities that improve consistency and efficiency across the analytics stack * Perform other duties as assigned ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)