Care Access is working to make the future of health better for all. They are seeking an experienced and detail-oriented Senior Data Engineer to design, develop, and maintain robust data pipelines that ensure reliable ingestion, transformation, and delivery of complex data across systems.
Responsibilities:
- 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
- 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
- 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
- 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
- Proactively suggest improvements to infrastructure, processes, and automation to improve system efficiency, reduce costs, and enhance performance
Requirements:
- 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
- Bachelor's or master's degree in computer science, Information Systems, Engineering, or a related field
- 5+ years of experience in data engineering with a proven track record of building cloud-based, production-grade data pipelines