Data Engineering Manager

Trella Health is hiring a Data Engineering Manager to lead its data engineering team and build a scalable healthcare data platform. The role combines hands-on technical leadership with designing and operating data pipelines, establishing architecture and governance, and supporting analytics, machine learning, and GenAI use cases while maintaining HIPAA and SOC 2 compliance.

Responsibilities:

• 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

Requirements:

• 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 platform technologies and transformation tools such as dbt or SQLMesh
• Strong ability to design scalable, modular codebases that promote maintainability, reuse, testing, and cross-team collaboration
• Experience implementing and leveraging data lineage to understand dependencies, assess upstream and downstream impact, and support governance and change management
• Solid understanding of data governance, data quality, and data security principles, including their application in regulated environments
• Proficiency in data modeling, database design, and data warehousing concepts for analytical and operational use cases
• Ability to partner effectively with DevOps to define and align on deployment standards, environment management, and operational best practices for data platforms and pipelines
• Working knowledge of healthcare data interoperability standards and APIs