Enterprise Service Platform Support Engineer

ExemplarITS•Plano, TX

9h•Onsite

About The Position

The Enterprise Service Platform Support Engineer ensures the reliability, performance, and scalability of a core enterprise service platform. The role supports a production environment built around distributed architectures, high-throughput data pipelines, Java and Spring Boot microservices, Kafka, MongoDB, and AWS. It bridges development and operations to keep enterprise services running and meet service-level agreements. The position is onsite in Plano, Texas, and is a long-term contract of 12 or more months. The engineer monitors and troubleshoots production systems, supports containerized cloud workloads, automates operational tasks, documents incidents and platform procedures, and works with engineering teams on permanent fixes. The role participates in a 24/7 on-call rotation. The technical stack includes Java 8/11+, Spring Boot, RESTful APIs, Apache Kafka, MongoDB, AWS services including EC2, EKS/ECS, MSK, DocumentDB, IAM, CloudWatch, and S3, as well as Docker, Kubernetes, Jenkins, Terraform or CloudFormation, Python, Bash, and monitoring/APM tools.

Requirements

At least 3 years of experience in production support, SRE, or DevOps roles supporting enterprise distributed platforms.
Strong ability to read and debug Java code and analyze thread dumps, heap dumps, and memory leaks.
Hands-on experience managing and troubleshooting distributed systems such as Kafka and NoSQL databases such as MongoDB.
Solid understanding of AWS core services, networking including VPC and Route53, and security including IAM.

Responsibilities

Monitor, troubleshoot, and resolve Level 2 and Level 3 incidents for enterprise-scale Java and Spring Boot microservices.
Manage and maintain Apache Kafka clusters, optimizing consumer group lags, partitions, and message retention.
Diagnose and resolve MongoDB performance issues, including slow queries, indexing strategies, and replication lag.
Participate in a 24/7 on-call rotation to maintain platform uptime and meet service-level agreements.
Support and monitor containerized workloads deployed across AWS environments, including EKS, ECS, or EC2.
Use AWS monitoring tools such as CloudWatch and X-Ray and APM tools such as Datadog, Dynatrace, or New Relic to identify platform bottlenecks.
Implement and manage infrastructure alerts to detect anomalies before they affect end users.
Build and maintain Python and Bash automation scripts for repetitive operational tasks and self-healing mechanisms.
Write Root Cause Analysis reports for major incidents and collaborate with engineering teams to deploy permanent bug fixes.
Maintain current runbooks, deployment documentation, and architectural diagrams.