Senior Data Engineer - API Platform Engineer - CDH

The Senior Data Engineer - API & AI Gateway Platform Engineer will design, develop, and support enterprise API and AI gateway platforms leveraging technologies such as Apigee (Edge, X, Hybrid), Palo Alto Prisma AIRS (Portkey), Akamai API Security and related integration frameworks. This role requires a combination of API & AI Gateway architecture, integration, platform engineering, and data enablement skills. This role operates with a high degree of autonomy and is expected to lead architectural decisions, influence platform strategy, and mentor other engineers in API & AI gateway platform best practices.

The ideal candidate will have experience building scalable API & AI gateway platforms, managing API lifecycle processes, and implementing secure, high-performing API & AI gateway solutions across cloud and hybrid environments. The Senior Data Engineer will partner with application teams, architects, and platform teams to enable consistent API & AI gateway delivery, governance, and operational excellence.

This role is part of the enterprise Information Security Modernization (ISM) program, supporting the evolution of secure, scalable API, AI gateway and API security platform capabilities. Participation in a rotating on-call support schedule is required.

Key responsibilities include:
• Lead design and architecture of enterprise API & AI gateway platform capabilities ensuring alignment with enterprise standards, scalability, and long-term maintainability.
• Build and manage scalable API proxies and services supporting REST and SOAP-based integrations.
• Implement API security frameworks including OAuth, JWT, API key management, mTLS, and secure communication protocols.
Implement and maintain enterprise AI gateway services.
• Develop and enforce API governance standards including versioning, lifecycle management, and API design best practices.
• Support API & AI gateway platform deployments across multi-cloud environments (GCP, Azure, on-prem) and hybrid architectures.
• Develop CI/CD pipelines and automation frameworks to enable consistent API & AI gateway deployments and lifecycle management.
• Configure and manage API traffic policies including rate limiting, caching, throttling, and load balancing to optimize performance and reliability.
• Monitor and analyze API performance using analytics, logging, and observability tools; identify and resolve performance or reliability issues.
• Integrate APIs with backend systems, microservices, and enterprise platforms to enable seamless data exchange.
• Participate in migration and modernization efforts including transition from legacy API platforms to cloud-native or hybrid API solutions.
• Ensure compliance with enterprise security, regulatory, and data privacy requirements including secure logging and data masking practices.
• Collaborate with developers, architects, and platform teams to translate business and technical requirements into scalable API solutions.
• Provide operational support including troubleshooting, incident response, and continuous improvement of API platform capabilities.
• Develop and maintain platform documentation, runbooks, and onboarding materials for internal users and developers.
• Support proof-of-concepts and innovation initiatives to evaluate new API and integration technologies.

This vacancy is not eligible for sponsorship/ we will not sponsor or transfer visas for this position. Also, Mayo Clinic DOES NOT participate in the F-1 STEM OPT extension program.

A Bachelor's degree in a relevant field such as engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative field and a minimum of five years of professional or research experience in data visualization, data engineering, analytical modeling techniques; OR an Associate’s degree in a relevant field such as engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative field and a minimum of seven years of professional or research experience in data visualization, data engineering, analytical modeling techniques. In-depth business or practice knowledge will also be considered.

Incumbent must have the ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes. Interpersonal skills, time management skills, and demonstrated experience working on cross functional teams are required. Requires strong analytical skills and the ability to identify and recommend solutions and a commitment to customer service. The position requires excellent verbal and written communication skills, attention to detail, and a high capacity for learning and problem resolution.

Advanced experience in SQL is required. Strong Experience in scripting languages such as Python, JavaScript, PHP, C++ or Java & API integration is required. Experience in hybrid data processing methods (batch and streaming) such as Apache Spark, Hive, Pig, Kafka is required. Experience with big data, statistics, and machine learning is required. The ability to navigate linux and windows operating systems is required. Knowledge of workflow scheduling (Apache Airflow Google Composer), Infrastructure as code (Kubernetes, Docker) CI/CD (Jenkins, Github Actions) is preferred. Experience in DataOps/DevOps and agile methodologies is preferred. Experience with hybrid data virtualization such as Denodo is preferred. Working knowledge of Tableau, Power BI, SAS, ThoughtSpot, DASH, d3, React, Snowflake, SSIS, and Google Big Query is preferred.
Google Cloud Platform (GCP) certification is preferred.

The preferred candidate will possess:

• Experience designing, deploying, or operating API management platforms or gateways (Apigee X experience preferred), including API proxy development, policy enforcement, and integration patterns.
• Strong experience with cloud-native infrastructure and container platforms (Google Cloud Platform, Kubernetes, Docker), including building and supporting scalable, highly available distributed systems.
• Experience with Infrastructure as Code (Terraform, Helm) and CI/CD pipeline development (Azure DevOps, Jenkins, GitHub Actions) to enable automated platform provisioning and deployment.
• Experience with networking concepts in cloud and hybrid environments, including DNS, load balancing, ingress/egress patterns, firewall rules, and private connectivity.
• Experience deploying and managing multi-cloud or hybrid environments, including integration between on-premises and cloud platforms.
• Google Cloud Platform (GCP) certification or Kubernetes certification is preferred.