Full-Time

Enterprise Architect

Event-Driven Architecture & Kafka

Confirmed live in the last 24 hours

WGU

WGU

Compensation Overview

$157k - $243.4kAnnually

+ Bonus

Senior, Expert

Salt Lake City, UT, USA + 1 more

More locations: Phoenix, AZ, USA

The job requires in-office presence at either the Salt Lake City or Phoenix office.

Category
Backend Engineering
Software Engineering
Required Skills
Kubernetes
Microsoft Azure
Apache Kafka
Microservices
AWS
Development Operations (DevOps)
Google Cloud Platform

You match the following WGU's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field, or related career experience
  • 8+ years of experience in enterprise architecture, with a focus on distributed systems and event-driven architectures.
  • Proven expertise in designing, implementing, and scaling Kafka-based solutions for real-time data processing.
  • Advanced knowledge of Apache Kafka, Kafka Streams, Kafka Connect, and related ecosystem components.
  • Proficiency in designing data streaming architectures, message-driven microservices, and asynchronous communication patterns.
  • Strong experience with DevOps practices, including Kafka cluster deployment, monitoring, and automation tools.
  • Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and container orchestration (e.g., Kubernetes) for Kafka management.
  • Exceptional analytical skills, strong communication abilities, and experience working with diverse, cross-functional teams.
Responsibilities
  • Develop and implement an enterprise-wide event-driven architecture strategy, utilizing Apache Kafka to support real-time data streaming and integration.
  • Design highly scalable and resilient data architectures that align with organizational goals, ensuring that systems are optimized for low-latency and high-throughput use cases.
  • Define and enforce EDA standards, protocols, and practices that facilitate reliable communication between services and systems.
  • Architect, deploy, and manage Kafka clusters and Kafka-based solutions for event streaming and processing across various business domains.
  • Design and implement Kafka topics, partitions, and schemas, ensuring optimal throughput and efficient data distribution.
  • Drive Kafka performance tuning, including managing retention policies, consumer lag monitoring, and replication configurations to support high availability and fault tolerance.
  • Work closely with application development, data engineering, and DevOps teams to ensure seamless integration and operationalization of Kafka and EDA components.
  • Partner with business stakeholders to identify use cases that benefit from event-driven approaches and translate them into architectural requirements.
  • Facilitate regular architecture review sessions to align Kafka and EDA implementation with broader enterprise architecture objectives.
  • Define data governance and security standards for event data, including access controls, data retention policies, and data encryption for compliance with organizational and regulatory standards.
  • Establish monitoring, alerting, and logging practices for Kafka infrastructure to ensure reliability, transparency, and quick incident resolution.
  • Research and propose new tools, technologies, and methodologies that complement event-driven architectures, such as Kafka Streams, Kafka Connect, and other data-streaming frameworks.
  • Promote best practices for EDA, including event modeling, message format standardization, and handling of event sourcing and eventual consistency.
  • Stay current with the latest developments in EDA, Kafka, and related open-source tools to continually improve the architecture's performance and adaptability.
Desired Qualifications
  • Certifications in enterprise architecture (e.g., TOGAF) or Kafka (e.g., Confluent Certified Developer for Apache Kafka).
  • Experience with complementary streaming tools, such as Spark, Flink, or Pulsar.
  • Understanding of data governance frameworks and practices for secure data streaming.

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