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About exacare ai

exacare ai is a leading health tech company on a mission to build the AI operating system for post-acute care. Our platform turns messy, unstructured referral packets into clear clinical insights and next steps, so teams can make faster, safer placement decisions with less administrative burden. Today, exacare ai powers more than 2,500 facilities, and is growing rapidly.

We recently raised a $30M Series A led by Insight Partners, and are bringing world-class talent together to transform healthcare. If you like building, learning, and want to make a real impact, come join us!

We’re looking for a Staff Data Engineer who thrives in an environment with strong ownership and can drive complex data initiatives from concept to production. You’ll build the pipelines, data models, and infrastructure that power our product, analytics, and AI workflows; turning complex healthcare data into reliable, usable foundations for our teams and customers.

What You’ll Do

• Own data initiatives end-to-end: Take a data problem through technical design, implementation, validation, production rollout, and ongoing operation, without requiring constant senior oversight.
• Build reliable data pipelines: Design and maintain scalable ingestion and transformation pipelines across application databases, APIs, third-party integrations, and healthcare data sources.
• Bring systems-to-workflow thinking: Connect data architecture, models, and integrations to how customers, operators, and internal teams use the resulting information.
• Design reusable data models: Create well-structured datasets and shared definitions that support product features, reporting, analytics, and machine learning.
• Own data quality and production readiness: Build validation, monitoring, alerting, and recovery into pipelines so teams can trust the accuracy, freshness, and completeness of their data.
• Scale performance and reliability: Improve processing efficiency, query performance, and infrastructure costs as data volume and product complexity grow.
• Collaborate across teams: Partner with product, operations, platform, ML, and other engineers to translate business needs into practical data solutions.
• Raise the engineering bar: Contribute to technical design, code reviews, documentation, and mentorship while establishing maintainable data engineering practices.

What You’ll Bring

• 7+ years of engineering experience with a focus on data engineering, data platforms, or backend systems involving substantial data processing.
• Strong proficiency with SQL and TypeScript, including building production pipelines and working with complex datasets.