At Trella Health, our mission is simple: empowering meaningful change in healthcare.
We are building AI-enabled intelligence and workflows that help healthcare organizations make smarter decisions, strengthen operations, and support healthier outcomes for patients. Our platform connects health systems and post-acute providers through actionable intelligence and connected workflows that improve how care is coordinated across the healthcare continuum.
That work starts with our people. Trellavators are collaborative, curious, and committed to doing meaningful work that makes a measurable impact. We move quickly, support each other, keep our commitments, and continuously look for better ways to serve our customers and one another.
If you are excited by the opportunity to grow your career while helping shape the future of healthcare intelligence, workflows, and outcomes, we would love to meet you.
Position Overview:
We’re looking for a Data Engineering Manager who still likes getting their hands dirty. You’ll lead our Data Engineering team and help build a healthcare data platform that’s fast, scalable, and ready for whatever we throw at it next.
Your job: design, build, and tune the pipelines and platforms that turn diverse healthcare data into analytics and insights people actually use. You’ll lead the team and roll up your sleeves alongside them, putting best-in-class architecture and governance in place while keeping us HIPAA and SOC 2 compliant.
The toolkit includes Databricks, Snowflake, and AWS. The problems are big, the data is complicated, and that's what makes it an exciting challenge to tackle.
Location: This role is remote with a strong preference for candidates within commuting distance of Atlanta, GA or Philadelphia, PA. We will also consider applicants based in other U.S. locations.
Reports to: CTO
As a Data Engineering Manager at Trella, you will:
Lead and scale a high-performing data engineering team through hands-on technical leadership, mentorship, and the establishment of best practices that drive innovation, collaboration, and continuous improvement
Architect, build, and evolve a centralized, cloud-native data platform supporting diverse healthcare datasets, including medical and Rx claims, EHR, CCLF, and BCDA data sources
Design, implement, and operate scalable data pipelines for ingestion, transformation, and normalization to support analytics, machine learning, and GenAI use cases
Implement flexible data ingestion patterns, including batch processing, streaming services, and FHIR-based APIs, to ingest data into the data lake
Optimize data platforms and pipelines for performance, reliability, scalability, and cost efficiency
Lead the design and enforcement of data governance standards, access controls, and encryption to meet HIPAA and SOC 2 compliance and certification requirements
Develop and maintain clear, comprehensive documentation covering data platform architecture, ETL/ELT processes, data lineage, and metadata
Partner cross-functionally with data science, QA, software engineering, product, and business stakeholders to deliver trusted, timely, and high-quality data assets
Collaborate with DevOps to enable automated, scalable deployment of data pipelines and platform components using CI/CD and infrastructure-as-code practices
Stay current with emerging trends and best practices in data engineering, healthcare data management, and advanced analytics, applying learnings to continuously improve the platform and team
This job might be a fit for you if you have:
8+ years of experience in data engineering, with demonstrated success coaching and developing technical talent and leading the design, delivery, and operation of cloud-based data platforms in production environments
Deep proficiency in Python, SQL, and modern ETL/ELT frameworks for building reliable, production-grade data workflows
Hands-on experience with Databricks, Snowflake, and AWS services (e.g., S3, Glue, Lambda, EMR), along with modern data…