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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Business Intelligence Developer - Founding Team - **Company:** Annuity Health, LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $120,000.0 - $225,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Azure, Python (Programming Language), Power BI, Standard Sql, SQL Databases, Delivery Pipeline, Snowflake, Microsoft Fabric, Pyspark, Databricks - **Published:** June 14, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=f578881b89bd5771 ## About the Role Do you have experience in SQL?, * 8+ years in BI/analytics with deep Power BI expertise - DAX, semantic modeling * Healthcare claims and payer data experience - you've worked with 835/837 transactions or adjacent claims data * Strong SQL and real experience working against a lakehouse or modern warehouse (Databricks, Fabric, Snowflake, or similar) * A track record of building reporting that external clients or executives actually relied on - not just internal dashboards Nice-to-haves: * Revenue cycle operations depth - denial management, AR follow-up, payer behavior. You know what a CARC code is without looking it up * Gold-layer or transformation ownership (PySpark, dbt, Delta Live Tables, or Fabric dataflows) * Fabric-specific depth - Direct Lake, OneLake, deployment pipelines * Experience standing up a BI function or being the first analytics hire somewhere ## Description * Own the semantic layer end to end - Power BI models on Databricks and Fabric, built for performance, maintainability, and trust * Define the company's metrics: one shared definition of AR days, denial rate, net collection rate, and the rest, so every team and every client sees the same truth * Build the provider-facing reporting our clients rely on - visually engaging, intuitive, fast, and credible enough to anchor a business review. Information design is part of the craft here. * Build the internal analytics our revenue cycle teams use to run their daily operation and to measure whether our automation is actually working * Establish our first data-analyst agents - automated analysis that monitors the data continuously, surfaces trends and anomalies, and drafts the first pass of insight before anyone thinks to ask. * Shape the gold layer as its primary consumer - and take ownership of transformations if that's in your toolkit * Set the BI standards, patterns, and review practices the function scales on as we grow * Sit with users on both sides - ops teams and client-facing leaders - and work problems, not ticket queues How we work This team is being built AI-native from day one: * We work problems, not tickets. You'll sit close to the people who use your work, watch how they actually operate, and reason from first principles about what to build. * AI tools are part of the craft. You should already be using AI daily to write DAX, SQL, and documentation faster - and be excited to help define what an AI data analyst looks like here. * You own what ships. Numbers that reach a client or drive an operational decision are correct, tested, and explainable. Speed matters; trust matters more. The stack: Power BI on Databricks and Microsoft Fabric, with SQL throughout and Python where it helps. Azure underneath. ## Related Videos - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [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) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [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) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [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) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)