Job Openings Enterprise Architect (23533-1) Maclean, VA

About the job Enterprise Architect (23533-1) Maclean, VA

If you post this job on a job board, please do not use company name or salary. Experience level: Mid-senior Experience required: 10 Years Education level: Bachelors degree Job function: Information Technology Industry: Information Technology and Services Pay rate : $70 per hour Total position: 1 Relocation assistance: No Visa sponsorship eligibility: No

This role is 100% Onsite

Please submit local candidates only!

Role: Enterprise Architect
Exp in Kafka: 10 & Above
Location: McLean, VA
Skills: Kafka, Salesforce Community Cloud, Application Integration Architecture

Job Summary

The Kafka Architect will be responsible for designing, implementing, and managing scalable, high-performance data streaming solutions using the Apache Kafka ecosystem, with a strong focus on Confluent Platform and Confluent Cloud.
The role demands deep expertise in real-time data processing, event-driven architecture, and integration with modern cloud and data platforms.
10 years of experience and above in Kafka architecture and implementation.
Deep expertise in Apache, Kafka confluent, Platform Confluent, Cloud Kafka Connect, Kafka Streams, ksqlDB, Zookeeper, KRaft
Experience with cloud platforms (AWS, GCP, Azure) and CICD pipelines.
Strong understanding of data integration tools (e.g., Snowflake, Databricks, Hadoop).
Familiarity with scripting (Shell, Python) and infrastructure-as-code (Terraform).
Financial services or credit union domain experience is highly preferred.

Architect and implement enterprise-grade Kafka solutions using Confluent Platform cloud.
Design and manage Kafka clusters, brokers, topics, and partitions for optimal performance and reliability.
Lead migration efforts from legacy messaging systems (e.g., IBM MQ, TIBCO) to Kafka.
Develop and optimize Kafka Streams, ksqlDB, Kafka Connect, and Flink-based pipelines.
Ensure high availability, disaster recovery, and security (RBAC, ACLs) of Kafka infrastructure.
Collaborate with data engineering, DevOps, and application teams to integrate Kafka into broader enterprise systems.
Monitor and troubleshoot Kafka environments using tools like Grafana, Prometheus, and Confluent Control Center.