Role Description This position is a Medicaid Subject Matter (SME) Expert for the Enterprise Data Warehouse supporting the State Medicaid program. This role requires significant expertise of Medicaid Enterprise System modules and data warehousing or decision support systems. The selected SME will provide guidance and direction to support a large data warehouse implementation for both DDI and maintenance & operations. - Provide direction, guidance and recommendations supporting decision making for large Medicaid data warehouse implementation and operations. - Lead and guide internal and external stakeholders to make determinations relating to complex processes involving claims processing/adjudication, recipient eligibility, provider enrollment, and third-party liability. - Proactively identify and understand state Medicaid agency data needs and determine the recommended solution to meet them with credible reason, justification and validated proof of concepts. - Direct technical and business teams on understanding healthcare topics and utilizing healthcare data appropriately. - Proactively suggest and recommend enhancements and improvements throughout the project processes, driven by Medicaid best practices, standards and policies. This is a telecommute position with some (<25%) required travel to Springfield, IL for onsite customer meetings. Qualifications - More than ten (10) years of experience in information technology with five (5) years of experience working directly with/for State Medicaid agencies or equivalent, supporting business initiatives through data analysis, writing business requirements and testing/validation of various systems. - More than 2 years of experience working CMS Federal Reporting MARS, PERM, T-MSIS, Quality of Care CMS Core Measure or similar projects. - Understanding of claims, recipient/eligibility, and provider/enrollment data processes. - Able to create and perform data analysis using SQL, Excel against data warehouses, utilizing large datasets. - Knowledge of the Centers for Medicare and Medicaid Services reporting requirements and the programs covered. - Excellent verbal/written communication and presentation skills, manager/executive/director-level client facing, team collaboration, and mentoring skills. - Ability to travel to Springfield, IL two (3) to three (4) times per year or as needed. Preferred Qualifications - Strong culture fit, demonstrating our culture values in action (Integrity, Compassion, Inclusion, Relationships, Innovation, and Performance). - Experience using JIRA, Rally, DevOps or equivalent. - Previous experience on large implementation or DDI project. - Located within driving distance (3 - 5 Hours) of Springfield, IL.

Our Company BrightSpring Health Services Overview We are seeking a highly skilled Senior Data Modeler to join our Data Engineering & Architecture team. This role will play a critical part not only in designing, developing, and maintaining logical and physical data models, but also in architecting, building, and optimizing the data pipelines and platforms that power our enterprise data warehouse, analytics ecosystem, and business intelligence solutions. This position ensures that data assets are structured, engineered, and delivered in a scalable, high performance, and user-friendly manner across the organization. Responsibilities - Design, implement, and optimize conceptual, logical, and physical data models to support enterprise reporting, analytics, and data science use cases. - Collaborate with data engineers, business analysts, and business stakeholders to translate business requirements into robust data structures. - Define and enforce data modeling standards, best practices, and naming conventions across the organization. - Develop and maintain data dictionaries, ER diagrams, and metadata documentation to ensure clarity and consistency. - Analyze existing data models and workflows to identify opportunities for improvement in performance, scalability, and maintainability. - Contribute to the development of enterprise data architecture patterns and reusable modeling frameworks. - Architect, build, and optimize scalable ETL/ELT pipelines using modern data engineering frameworks and cloud technologies. - Lead the design and development of distributed data processing workflows using Databricks, PySpark, Azure SQL and/or Azure Synapse. - Develop and optimize data ingestion frameworks (batch and streaming) from diverse sources including FHIR, APIs, files, databases, and event streams. - Ensure data pipelines meet enterprise standards for performance, reliability, observability, and recoverability. - Perform advanced SQL, PySpark, or Python optimization to maximize query speed and dataset availability for analytics and downstream applications. - Oversee data lake and data warehouse architecture, including partitioning strategies, delta lake management, schema evolution, and performance tuning. - Troubleshoot, diagnose, and resolve complex data engineering and pipeline issues across cloud environments. - Mentor junior engineers and modelers, influencing engineering patterns, coding standards, and architectural direction. - Collaborate with security teams to implement proper access controls, encryption, secrets management, and compliance processes. Qualifications - Bachelor’s degree in Computer Science, Information Systems, Data Management, or related field (or equivalent experience). - 7–10 years of experience in data modeling, data engineering, dimensional modeling, or data architecture roles. - Strong knowledge of relational, dimensional, and NoSQL data modeling techniques. - Advanced SQL skills and experience designing for cloud data platforms (Databricks, Synapse, Azure SQL Databases, Redshift, BigQuery, or similar). - Expertise in building scalable ETL/ELT processes using modern data engineering tools (Azure Data Factory, Databricks, Synapse Pipelines, SSIS, etc.). - Strong proficiency with Python, PySpark, or Scala for data engineering and scripting. - Hands-on experience with Azure cloud data services: Azure Data Factory, Azure SQL Database, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Databricks. - Experience designing and optimizing data lakes, delta lakehouse architectures, and large-scale distributed data systems. - Experience working with DevOps concepts—CI/CD pipelines, Git branching strategies, automated testing, and deployment. - Ability to orchestrate and influence remote teams, ensuring successful implementation of complex data solutions. - Detail-oriented with excellent organizational skills. - Effective working in a cross-functional, dynamic, and remote environment. - Strategic thinker with the ability to balance short-term deliverables with long-term platform evolution. Preferred - Hands-on experience designing, building, and operationalizing unified data platforms, including semantic layers, ontologies, and knowledge graphs, to enable AI/ML product development. - Experience with enterprise-scale analytics environments and BI tools (Power BI, Qlik, Tableau, Databricks AI/BI Dashboards). - Exposure to data governance, data cataloging, and MDM practices. - Knowledge of data vault modeling, star schema, and snowflake modeling. - Experience designing real-time/streaming data pipelines (Kafka, Event Hubs, Spark Streaming, etc.). - Familiarity with API platforms and tools such as Postman or API gateways. - Experience tuning large-scale Spark workloads and optimizing cloud compute costs. - Strong communication and collaboration skills across both technical and non-technical teams. Key Competencies - Analytical and meticulous mindset with a strong ability to solve complex data design and engineering challenges. - Ability to balance short-term deliverables with long-term enterprise strategy. - Strong documentation and communication skills for presenting technical concepts to non-technical audiences. - Leadership qualities with the ability to mentor and guide junior team members. - Ability to think holistically across data modeling, data engineering, and data architecture disciplines. About our Line of Business BrightSpring Health Services provides complementary home- and community-based pharmacy and provider health solutions for complex populations in need of specialized and/or chronic care. Through the Company’s service lines, including pharmacy, home health care and rehabilitation, we provide comprehensive and more integrated care and clinical solutions in all 50 states to over 450,000 customers, clients and patients daily. BrightSpring has consistently demonstrated strong and industry-leading quality metrics across its services lines, while improving the health and quality of life for high-need individuals and reducing overall healthcare system costs. For more information, please visit www.brightspringhealth.com. Follow us on Facebook, LinkedIn, and X.

• Implement robust data ingestion strategies using GA4 and GTM for data collection. • Architect cloud storage and data pipelines on Google Cloud Platform using BigQuery and Pub/Sub. • Drive data consumption and visualization via Looker and LookML for complex data structuring. • Orchestrate ETL and reverse ETL workflows, aggregating data from varied sources into cohesive warehouses. • Enable lifecycle marketing and experimentation, establishing identity resolution and audience syncing capabilities.

• Design, build, and maintain scalable data platforms using AWS to support analytics, machine learning, and emerging generative AI use cases • Collaborate with data scientists, analysts, and engineering teams to translate business and AI requirements into scalable data solutions • Ensure data quality, performance, and cost efficiency across the platform • Work with large-scale datasets to build and optimize data pipelines using AWS services such as EMR (Spark, Trino), S3, Glue, Athena, and Airflow • Design and manage lakehouse architectures, using technologies like Apache Iceberg and Glue Catalog • Support machine learning and LLM projects by preparing and delivering datasets for use in Amazon SageMaker and Amazon Bedrock