Senior Data Engineer

About this role

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 .

How This Role Makes a Difference

The Senior Data Engineeris responsible for designing, developing, implementing, and maintaining scalable data pipelines and enterprise data solutions that support the organization's operational, analytical, and reporting needs. This position oversees the ingestion, transformation, integration, and delivery of complex data from multiple sources to ensure the availability, reliability, and integrity of enterprise data assets. The Senior Data Engineer collaborates with cross-functional stakeholders to develop modern data architectures, optimize data processing workflows, and enhance platform performance using industry best practices and cloud-based technologies. This role provides technical leadership in advancing the organization's data infrastructure, supporting data governance initiatives, and delivering high-quality data solutions that enable informed business decision-making.

How You'll Make An Impact

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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.

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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.

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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.

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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.

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Continuous Improvement:
• Proactively suggest improvements to infrastructure, processes, and automation to improve system efficiency, reduce costs, and enhance performance.

The Expertise Required

• 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

• Minimum Education:
• Bachelor’s or master’s degree in computer science, Information Systems, Engineering, or a related field.

• Minimum Experience:

• 5+ years of experience in data engineering with a proven track record of building cloud-based, production-grade data pipelines.

• 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.

How We Work Together

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Location: Remote within the United States. This role requires 100% of work to be performed in a remote office environment.

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Travel: This is a remote position with less than 10% travel requirements. Occasional planned travel may be required as part of the role.

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Physical demands associated with this position Include: The ability to use keyboards and other computer equipment.

The expected pay range for this role is $120,000 - $160,000 USD per year for full time team members.

Benefits & Perks (US Full Time Employees)

• Paid Time Off (PTO) and Company Paid Holidays

• 100% Employer paid medical, dental, and vision insurance plan options

• Health Savings Account and Flexible Spending Accounts

• Bi-weekly HSA employer contribution

• Company paid Short-Term Disability and Long-Term Disability

• 401(k) Retirement Plan, with Company Match

Mandatory Employer Disclosures

Notice to Illinois applicants: Applicants are not obligated to disclose expunged juvenile records or adjudication, arrest, or conviction.
Notice to Connecticut applicants: Care Access may require applicants to submit to a urinalysis drug test in connection with an application for employment.
Notice to Arizona, Georgia, Indiana, and North Dakota applicants: Care Access complies with applicable laws prohibiting smoking in and around places of employment.
Notice to…