

Principal Data Engineer
Job Description
Transcarent is aligned with those who pay for healthcare and takes accountability for results – offering at-risk pricing models and transparent impact reporting to ensure incentives support a measurably better experience, better health, and lower costs.
Responsibilities
Lead the Design and Implementation: Using modern data architecture principles, architect and implement cutting-edge data processing platforms and enterprise-wide data solutions.
Scale Data Platform: Develop a scalable Platform for optimal data extraction, transformation, and loading from various sources, ensuring data integrity and accessibility.
AI / ML platform: Design and build scalable AI and ML platforms to support Transcarent use cases.
Collaborate Across Teams: Partner with Executive, Product, Clinical, Data, and Design teams to meet their data infrastructure needs, supporting them with technical expertise.
Optimize Data Pipelines: Build and optimize complex data pipelines, ensuring high performance, reliability, and scalability.
Innovate and Automate: Create and maintain data tools and pipelines that empower analytics, data science, and other teams to drive innovation and operational excellence.
Mentor and Lead: Provide technical leadership and mentorship to the data engineering team, fostering a culture of continuous learning and improvement.
Job Requirements
Experienced: 10+ years of experience in data engineering with a strong background in building and scaling data architectures in complex environments. Healthcare experience is a plus.
Technical Expertise: Advanced working knowledge of SQL, relational databases, and big data tools (e.g., Spark, Kafka). Proficient in cloud-based data warehousing (e.g., Snowflake) and cloud services (e.g., AWS). Proficient in understanding of AI / ML workflows, etc.,
Architectural Visionary: Demonstrated experience in service-oriented and event-based architecture with strong API development skills.
Problem Solver: Ability to manage and optimize processes supporting data transformation, metadata management, and workload management.
Collaborative Leader: Strong communication skills with the ability to present ideas clearly and lead cross-functional teams effectively.
Project Management: Strong project management and organizational skills, capable of leading multiple projects simultaneously.