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O'Reilly Auto Parts

Automotive parts retailer with nationwide stores

Systems Engineer Platform: Messaging Platform

Platform EngineeringConfirmed live in the last 24 hours
Full-timeSpringfield, MO, USA

About the Job

Requirements

  • At least 3 years of experience with enterprise messaging platforms such as Kafka and Pub/Sub, including Kafka brokers, partitions, replication, schema management, streams, and connectors.
  • Experience designing high-throughput, low-latency event-driven systems with governance, topic management, and access control.
  • Hands-on experience with GCP messaging services, including Pub/Sub and Eventarc, and hybrid architectures involving secure connectivity, IAM, and multi-region designs.
  • Proficiency with Infrastructure as Code and automation using Terraform, Kubernetes, Helm, CI/CD tools, and GitOps-based configuration management.
  • Background in security and compliance, including TLS/mTLS encryption, SASL and IAM authentication, and PCI, SOC 2, and HIPAA standards.
  • Experience implementing observability using Prometheus, Grafana, ELK, and GCP tools, including monitoring lag, throughput, and distributed tracing.
  • Performance tuning and reliability practices, including scaling, backpressure handling, dead-letter queues, retries, and cross-region replication.
  • Experience enabling developers through reusable tools, self-service platforms, schema governance, and event-driven best practices.
  • Ability to evaluate and prototype messaging technologies such as Pulsar and RabbitMQ, lead proofs of concept, and drive adoption of modern streaming and data integration patterns.

Responsibilities

  • Design and operate scalable messaging platforms, including Kafka, Pub/Sub, and legacy message queues, for high-throughput, low-latency event streaming.
  • Manage topics, schemas such as Avro, JSON, and Protobuf, connectors, and stream processing such as Kafka Streams and KSQLDB.
  • Enforce governance for naming, retention, access control, and multi-tenancy, and ensure reliable delivery through retries, dead-letter queues, idempotency, and exactly-once processing.
  • Automate messaging infrastructure using Terraform, Helm, and Kubernetes such as Strimzi, with Git-based configuration management.
  • Build CI/CD pipelines for deployments, upgrades, and topic provisioning, including drift detection and self-healing workflows.
  • Implement secure messaging with GCP, LDAP, and Kerberos IAM integrations, TLS/mTLS, and access control lists; align systems with PCI and HIPAA compliance and Zero Trust principles, including data classification, logging, and anomaly detection.
  • Establish observability using Prometheus, Grafana, ELK, or GCP tools; monitor SLAs/SLOs, consumer lag, broker health, and replication; lead incident response, root-cause analysis, and disaster recovery planning.
  • Enable teams with reusable connectors, SDKs, and event-driven patterns; provide guidance on schema evolution, idempotency, and domain-driven event design using self-service tools and documentation.
  • Drive migration from legacy systems to modern streaming platforms and evaluate technologies such as Pulsar and Redpanda.
  • Lead migration strategies, dual-write patterns, and multi-region replication.
  • Collaborate with cross-functional teams on architecture and governance, contribute to event-driven and data mesh strategies, and mentor engineers while promoting best practices.

Desired Qualifications

  • Experience running Kafka on Kubernetes using Strimzi or Confluent Operator, including scaling, configuration, and multi-tenant architectures.
  • Foundation in event-driven architecture, microservices communication, and asynchronous messaging patterns.
  • Hands-on experience with real-time processing tools such as Kafka Streams, Flink, and Spark, and Kafka Connect integrations such as Debezium, JDBC, and Elasticsearch.
  • Proficiency in schema management with Avro and Protobuf and schema registries such as Confluent and Apicurio.
  • Familiarity with Docker, Kubernetes (GKE), and service mesh technologies such as Istio and Linkerd for secure, cloud-native deployments.
  • Experience with cloud messaging and analytics tools such as GCP Pub/Sub and Dataflow, and migration from legacy systems such as IBM MQ and RabbitMQ.
  • Knowledge of security and access control, including ACLs, SASL/SCRAM, Kerberos, and IAM, and message delivery semantics such as at-least-once and exactly-once.
  • Experience with observability tools such as Prometheus, Grafana, and GCP Monitoring; CI/CD automation for Kafka resources; and data governance tools such as Dataplex and Collibra.
  • Industry experience and certifications, and ability to lead design discussions, mentor teams, and work in agile environments.

About the Company

O'Reilly Auto Parts

Automotive parts retailer with nationwide stores

O'Reilly Auto Parts runs a large network of auto parts retail stores and distribution centers, selling automotive parts and supplies to retail customers and professional installers. It stocks a wide range of parts and related items and helps customers choose the right parts with knowledgeable staff and efficient service. The company differentiates itself through its nationwide store footprint, emphasis on customer service, and a culture focused on growth and development, aiming to be the dominant supplier in its markets by offering the best price, quality, and service. Its goal is to become the leading auto parts supplier in its market areas by delivering strong prices, quality parts, and high levels of service.

Company size
10,001+
Company stage
IPO
Headquarters
Springfield, IL
Founded
1957

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