Sr. Data Engineer (remote)

At Claritev, we pride ourselves on being a dynamic team of innovative professionals. Our purpose is simple - we strive to bend the cost curve in healthcare for all. Our dedication to service excellence extends to all our stakeholders - internal and external - driving us to consistently exceed expectations. We are intentionally bold, we foster innovation, we nurture accountability, we champion diversity, and empower each other to illuminate our collective potential.

Be part of our amazing transformational journey as we optimize the opportunity towards becoming a leading technology, data, and innovation voice in healthcare. Onward and Upward!!!

JOB SUMMARY: We are building a next generation analytics platform that ingests provider claims and clinical data in (near) real time, standardizes it into a Common Data Model, and powers insights across OCI, Azure and AWS. As a Senior Data Engineer,you will be a hands-on technical leader who drives the design, development, and optimization of this platform from ingestion through curated data, with an emphasis on performance, data quality, governance, and security (HIPAA/HITRUST).

JOB ROLES AND RESPONSIBILITIES:

• Collaborate with business users, technology teams, and executives to understand their data needs to create innovative solutions.
• Guiding decisions and establishing best practices on data integration/engineering, as well as the future of our data infrastructure.
• Document high- and low-level technical design.
• Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines.
• Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management.
• Thinking through long-term impacts of key design decisions and handling failure scenarios.
• Ability to provide mentoring to a team of data engineers.
• Research and learn new technologies and processes as part of continuous improvement.
• Work with data science, data engineering, and software engineering teams to automate data analysis and visualization, advise on data transformation, and explore ways to design and develop data infrastructure Requirements