Data Warehouse Engineer

At Modivcare, our mission is to connect people to the care they need. Every report, dashboard, operational workflow, and AI initiative starts with trusted data. As a Cloud Data Warehouse Engineer, you'll build scalable data pipelines, cloud data warehouse solutions, and transformation frameworks that enable smarter decisions and improve healthcare outcomes for millions of members. We're looking for an experienced engineer with strong, hands-on dbt Core experience who enjoys building modern cloud data platforms and turning complex data into business value. Your work will directly influence how business leaders, operations teams, and analytics partners make decisions every day. You'll help modernize our enterprise data platform by building trusted, scalable data products that improve reporting, enable self-service analytics, and support AI initiatives. This is an opportunity to solve complex technical challenges while making a measurable impact on the healthcare experience for the people we serve. This role… Design, develop, and maintain dbt projects, models, macros, snapshots, tests, and reusable transformation frameworks. Build and maintain enterprise data transformation pipelines using dbt Core and advanced SQL. Develop reusable business logic and data models that support reporting, self-service analytics, operational applications, and AI initiatives. Implement dbt best practices including modular design, testing, documentation, lineage tracking, and source control. Optimize dbt models and transformation workloads for performance, scalability, and maintainability. Support CI/CD deployment processes and automated testing for dbt projects. Collaborate with business and technical teams to translate requirements into scalable and reusable transformation logic. Data Modeling & Data Warehouse Development Develop and maintain cloud data warehouse solutions using AWS services including Redshift, S3, Glue, Athena, Lambda, and Step Functions. Design and maintain dimensional data models supporting reporting, self-service analytics, and operational data needs. Build and maintain fact tables, dimensions, star schemas, snowflake schemas, and slowly changing dimensions (SCDs). Develop curated data marts and trusted datasets for reporting, analytics, and downstream applications. Partner with business and technical teams to translate requirements into scalable and reusable data models. Optimize data structures and query performance for large-scale analytical workloads. Follow established standards and best practices for data modeling, SQL development, and data warehouse design. Design, build, and maintain batch and near real-time data pipelines supporting enterprise data integration requirements. Develop ELT/ETL workflows using AWS services, dbt, SQL, and Python. Integrate data from operational systems, APIs, SaaS applications, healthcare platforms, and third-party data providers. Support ingestion and transformation of structured, semi-structured, and unstructured data. Optimize data processing workflows for scalability, reliability, and cost efficiency. Troubleshoot and resolve data pipeline and data warehouse performance issues. Partner with application teams, business stakeholders, BI developers, and analytics teams to understand data requirements. Deliver trusted and well-documented datasets that support reporting and self-service analytics. Participate in Agile development processes including sprint planning, estimation, code reviews, testing, and release management. Work effectively with remote and offshore teams to deliver data platform initiatives. We are interested in speaking with individuals with the following… Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field; equivalent combination of education and experience will be considered. Five (5) or more years of experience in data warehousing, cloud data engineering, or related data platform roles. Experience designing and developing enterprise cloud data warehouse solutions. Experience building enterprise ELT/ETL solutions and data integration pipelines. Experience working with modern cloud data warehouse environments. Experience supporting reporting, business intelligence, self-service analytics, and enterprise data platforms. Experience working in healthcare or another regulated industry is preferred. Strong hands-on experience with dbt Core, including development of models, macros, snapshots, tests, documentation, lineage, and reusable transformation frameworks. Advanced knowledge of SQL, including complex joins, window functions, common table expressions (CTEs), analytical transformations, query tuning, and performance optimization. Knowledge of dimensional data modeling techniques, including fact tables, dimensions, star schemas, snowflake schemas, and slowly changing dimensions (SCDs). Proficiency with Amazon Redshift and modern cloud data warehouse technologies. Knowledge of AWS cloud services, including Redshift, S3, Glue, Lambda, Athena, and Step Functions. Proficiency in Python for data engineering, automation, and scripting. Knowledge of Git, CI/CD, and modern software development best practices. Ability to design, develop, and optimize batch, micro-batch, and near real-time data pipelines. Ability to build curated data marts and trusted datasets that support reporting, self-service analytics, and downstream applications. Strong analytical, problem-solving, communication, collaboration, and organizational skills. Ability to work effectively in Agile environments and collaborate with remote and offshore teams. The physical demands described are representative of those that must be met by an employee to successfully perform the essential functions of the position. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform the essential functions of the job. Primarily seated work; extensive computer and telephone use; occasional standing, walking, reaching, bending, and lifting up to 10 lbs. #J-18808-Ljbffr