Similar Jobs
_0.png)
About Us
Zelis is modernizing the healthcare financial experience in the United States (U.S.) by providing a connected platform that bridges the gaps and aligns interests across payers, providers, and healthcare consumers. This platform serves more than 750 payers, including the top 5 health plans, BCBS insurers, regional health plans, TPAs and self-insured employers, and millions of healthcare providers and consumers in the U.S. Zelis sees across the system to identify, optimize, and solve problems holistically with technology built by healthcare experts—driving real, measurable results for clients.
Why We Do What We Do
In the U.S., consumers, payers, and providers face significant challenges throughout the healthcare financial journey. Zelis helps streamline the process by offering solutions that improve transparency, efficiency, and communication among all parties involved. By addressing the obstacles that patients face in accessing care, navigating the intricacies of insurance claims, and the logistical challenges healthcare providers encounter with processing payments, Zelis aims to create a more seamless and effective healthcare financial system.
Zelis India plays a crucial role in this mission by supporting various initiatives that enhance the healthcare financial experience. The local team contributes to the development and implementation of innovative solutions, ensuring that technology and processes are optimized for efficiency and effectiveness. Beyond operational expertise, Zelis India cultivates a collaborative work culture, leadership development, and global exposure, creating a dynamic environment for professional growth. With hybrid work flexibility, comprehensive healthcare benefits, financial wellness programs, and cultural celebrations, we foster a holistic workplace experience. Additionally, the team plays a vital role in maintaining high standards of service delivery and contributes to Zelis’ award-winning culture.
Position Overview
Key Responsibilities:
Data Platform Support: Provide technical support (L2 & L3) and maintenance for our data platform, including data ingestion pipelines, data storage systems, and data processing workflows. Monitor system health, identify performance bottlenecks, and implement optimizations to ensure scalability and reliability. Expert with DW concepts, implementation using Snowflake and other MPP databases.
ML Ops Support: Support the end-to-end machine learning lifecycle, from model development to deployment and monitoring. Collaborate with data scientists and ML engineers to deploy machine learning models into production environments, manage model versions, and implement automated testing and monitoring solutions.
Incident Management: Respond to production incidents and service interruptions in a timely manner, troubleshoot root causes, and implement corrective actions to minimize downtime and ensure service availability as per defined SLA. Develop and maintain runbooks and documentation for incident response procedures.
Performance Monitoring and Optimization: Implement monitoring tools and metrics to track the performance and health of data and ML systems. Analyze system logs and metrics to proactively identify issues, optimize resource utilization, and improve overall system efficiency.
Automation and Tooling: Develop and maintain automation scripts and tools to streamline routine tasks, such as data ingestion, ETL processes, model deployment, and monitoring. Implement CI/CD pipelines for deploying code changes and model updates with minimal downtime.
Cross-Functional Collaboration: Work closely with data engineering, data science, software engineering, and DevOps teams to ensure seamless integration of data and ML solutions into our production environment. Participate in agile ceremonies and collaborate on cross-functional projects to deliver high-quality solutions.
Qualifications:
Bachelor's or Master's degree in computer science, engineering, or a related field.
Strong understanding of data management principles, including data modeling, data warehousing, and ETL processes. Work experience around Snowflake, DBT, Azure data services is preferred.
Experience with cloud platforms such as AWS (Amazon Web Services) or Azure, and proficiency in SQL and scripting languages such as Python or Shell scripting.
Familiarity with ML Ops tools and frameworks, such as MLflow.
Hands-on experience with containerization technologies (Docker, Kubernetes) and infrastructure-as-code tools (Terraform, Ansible) is a plus.
Excellent troubleshooting and problem-solving skills, with the ability to quickly diagnose and resolve complex technical issues.
Strong communication and collaboration skills, with the ability to work effectively in a fast-paced, cross-functional team environment.
Experience in healthcare or fintech industries is preferred, with knowledge of industry regulations and compliance requirements.
