Senior Data Modeler

BrightSpring Health Services

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.

• 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.

• Bachelors degree in Computer Science Information Systems Data Management or related field (or equivalent experience).
• 710 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 conceptsCI/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.