Lead Lead Application Engineer - R01556584
Saint Louis, Missouri, United States
AI & Data Engineering – AI & Data Engineering : Data Engineering /
Contingent Worker /
Hybrid
About Brillio:
Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.
Consultant
Primary Skills
- Weblogic Administration, Postgres, MongoDB, WebSphere, NGNIX, Apache Tomcat, Oracle DBA, BIZTALK, Oracle PL/SQL, Informix DBA, CFI/MFT, DB2, SQL DBA, Middleware, MySQL
Specialization
- Database & Middleware Support: Engineer, Systems & Storage
Job requirements
- Lead Application Engineer
- Location: Coppel, TX or Ney York, NY - Hybrid with 2/3 days per week WFO
- Experience: 8–10 years in software engineering with 4+ years building data pipelines and distributed applications using Kafka and Python.
- Role Summary:
- Owns the end-to-end technical delivery for onboarding new claim platforms (Facets, ABS, Excelys) into the Pisces orchestration hub, ensuring scalable, reliable, and governed data integration.
- Responsibilities:
- Design, develop, and deploy Python-based Kafka consumer and producer jobs.
- Collaborate with architects to implement reusable orchestration patterns and a common data model.
- Optimize data flow performance, fault tolerance, and recovery processes.
- Integrate vendor-facing Kafka topics with external clusters via topic mirroring.
- Support production readiness, observability, and performance optimization.
- Skill Set & Tech Stack:
- Python, Kafka, Kubernetes, Docker, MongoDB, Oracle SQL, Jenkins, Prometheus/Grafana, ELK.
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