Data Engineer 3

Accountabilities: In this role, you will build and optimize data infrastructure, develop reliable processing workflows, and ensure that healthcare data is accessible, accurate, and secure. Your main responsibilities will include: Design, develop, and implement scalable data pipelines for ingesting, transforming, and processing healthcare datasets. Build and maintain ETL/ELT workflows supporting the integration and processing of CMS and Medicaid data. Develop and manage data processing workflows using Databricks and distributed computing technologies. Create data transformation and analytics solutions using Python, PySpark, and SQL. Ensure data quality, consistency, integrity, and governance across multiple systems and platforms. Optimize data pipeline performance and large-scale processing workloads to improve efficiency and reliability. Collaborate with analytics, engineering, and DevOps teams to support data platform operations and continuous improvements. Maintain clear technical documentation covering data architecture, data models, pipeline processes, and workflows. Implement appropriate security practices and support compliance with healthcare data privacy and protection requirements. Requirements The ideal candidate is an experienced data engineering professional with strong programming skills, cloud analytics expertise, and practical knowledge of healthcare data environments. The following qualifications and capabilities are required: Bachelor's degree with at least 5 years of relevant professional experience, or a Master's degree with at least 3 years of relevant experience. Previous experience working with CMS systems and/or Medicaid datasets. Hands-on experience with cloud-based data analytics platforms, particularly Databricks. Strong programming expertise in Python, PySpark, and SQL. Proven experience designing and developing distributed data processing pipelines. Experience handling, transforming, and analyzing large-scale healthcare datasets. Strong understanding of ETL/ELT architecture, development, and implementation. Ability to design scalable, reliable, and efficient data solutions. Strong analytical and problem-solving skills, with attention to data quality and technical accuracy. Effective communication and collaboration skills to work across analytics, engineering, and DevOps teams. U.S. work authorization is required. Ability to obtain and maintain a Public Trust clearance, which may include fingerprinting. Additional qualifications considered an advantage include: Experience implementing data lake or lakehouse architectures. Familiarity with healthcare data interoperability standards. Benefits Competitive annual base salary ranging from $95,000 to $120,000 , with potential variation of up to 10% based on geographic location. Comprehensive employee benefits package. Flexible work schedules to support work-life balance. Remote working opportunity. Professional development and continuous learning opportunities. Wellbeing programs designed to support employees' personal and professional needs. Inclusive working environment that values diverse perspectives and collaboration. Opportunity to contribute to meaningful healthcare data initiatives through modern cloud technologies.