Senior Data Engineer

About Care Access Care Access is working to make the future of health better for all. With hundreds of research locations, mobile clinics, and clinicians across the globe, we bring world-class research and health services directly to communities that often face barriers to care. We are dedicated to ensuring that every person has the opportunity to understand their health, access the care they need, and contribute to the medical breakthroughs of tomorrow. With programs like Future of Medicine , which makes advanced health screenings and research opportunities accessible to communities worldwide, and Difference Makers , which supports local leaders to expand their community health and wellbeing efforts, we put people at the heart of medical progress. Through partnerships, technology, and perseverance, we are reimagining how clinical research and health services reach the world. Together, we are building a future of health that is better and more accessible for all. To learn more about Care Access, visit www.CareAccess.com . How This Role Makes a Difference We are seeking an experienced and detail-oriented professional to join our team as a Senior Data Engineer . In this pivotal role, you will be responsible for designing, developing, and maintaining robust data pipelines that ensure the reliable ingestion, transformation, and delivery of complex data (demographics, medical, financial, marketing, etc.) across systems. The ideal candidate will bring deep expertise in Databricks, SQL, and modern data engineering practices, along with strong collaboration skills to help drive excellence across our data infrastructure. How You'll Make An Impact Data Engineering Strategy and Architecture: Design and implement scalable, reliable, and efficient data pipelines to support clinical, operational, and business needs. Develop and maintain architecture standards, reusable frameworks, and best practices across data engineering workflows. Build automated systems for data ingestion, transformation, and orchestration leveraging cloud-native and open-source tools. Data Infrastructure and Performance Optimization: Optimize data storage and processing in data lakes and cloud data warehouses (Azure, Databricks). Develop and monitor batch and streaming data processes to ensure data accuracy, consistency, and timeliness. Maintain documentation and lineage tracking across datasets and pipelines to support transparency and governance. Collaboration and Stakeholder Engagement: Work cross-functionally with analysts, data scientists, software engineers, and business stakeholders to understand data requirements and deliver fit-for-purpose data solutions. Review and refine work completed by other team members, ensuring quality and performance standards are met. Provide technical mentorship to junior team members and collaborate with contractors and third-party vendors to extend engineering capacity Technology and Tools: Use Databricks, DBT, Azure Data Factory, and SQL to architect and deploy robust data engineering solutions. Integrate APIs, structured/unstructured data sources, and third-party systems into centralized data platforms. Evaluate and implement new technologies to enhance the scalability, observability, and automation of data operations. Other Responsibilities: Continuous Improvement: Proactively suggest improvements to infrastructure, processes, and automation to improve system efficiency, reduce costs, and enhance performance. The Expertise Required Strong expertise in Databricks, SQL, dbt, Python, and cloud data ecosystems such as Azure. Experience working with structured and semi-structured data from diverse domains. Familiarity with CI/CD pipelines, orchestration tools (e.g., Airflow, Azure Data Factory), and modern software engineering practices. Strong analytical and problem-solving skills, with the ability to address complex data challenges and drive toward scalable solutions. Certifications/Licenses, Education, and Experience: Bachelor’s