Systems Engineer - IT Data Management

AutoZone•Memphis, TN

About The Position

The AutoZone Data Management team is seeking an experienced Systems Engineer to join a growing technology team supporting key business initiatives. This role focuses on Python-based engineering, automation, data workflow support, and Linux/Unix system administration. Experience with Java/J2EE applications is also beneficial. The Systems Engineer will support the transition, implementation, and production operation of services and applications, with an emphasis on Python development, automation scripting, ETL/data integration workflows, REST APIs, Oracle stored procedures, Infrastructure as Code (Terraform), AWX-based automation, AI-enabled engineering, capacity planning, performance management, and a working understanding of Java/J2EE applications. The role requires analyzing situations, making decisions within a subsystem, applying subject matter expertise, estimating and planning work, solving technical problems with limited supervision, and communicating effectively with other teams and business groups.

Requirements

Bachelor’s Degree in MIS, Information Technology, Computer Science, or related field required.
Typically 4–7 years of experience in the role of a Software Engineer, Systems Engineer, Developer, or similar technical role.
Strong software development background in Python, with the ability to understand, troubleshoot, and support Java/J2EE technologies.
Experience developing Python-based services, scripts, or data workflows; familiarity with Java/J2EE, Spring Boot, REST APIs, Oracle stored procedures, and application support or enhancement work.
Proficiency with CI/CD pipelines, version control systems, build/deployment practices, Infrastructure as Code practices such as Terraform, AWX automation, and release support activities.
Experience with ETL, data integration, or data pipeline support using tools or platforms such as BigQuery, Dataflow, Cloud Composer, Python, SQL, or similar technologies.
Familiarity with AI-enabled development or operational practices, including AI-assisted coding, prompt-based analysis, model integration, or AI/ML pipeline concepts.
Ability to work independently with little to no supervision while managing own tasks, goals, training, and development.
Ability to communicate effectively with other engineering teams, support teams, and business groups.
Ability to estimate, plan, and execute assigned work within the engineer’s technical domain.
Ability to guide newer AutoZoners and/or interns when appropriate, without formal team lead expectations.

Nice To Haves

Experience designing, building, supporting, or maintaining cloud-native applications in Google Cloud, including Infrastructure as Code or Terraform-managed environments where applicable, is preferred.
Google Cloud Associate Cloud Engineer certification preferred; Google Cloud Professional Data Engineer or Professional Machine Learning Engineer certification is a plus for roles with data, ETL, automation, or AI responsibilities.
Linux/Unix system administration experience is a plus, particularly hands-on knowledge of shell scripting, file permissions, process management, cron or enterprise job scheduling, log analysis, troubleshooting, and production server support to enable automation and improve operational reliability.
Experience with messaging brokers such as Kafka, ActiveMQ, or RabbitMQ.
Experience with automation scripting, job scheduling, workflow automation, repeatable operational runbooks, Infrastructure as Code concepts, Terraform, or AWX is preferred.
Experience with NoSQL databases, cloud-native application patterns, Couchbase, BigQuery, PHP, Python, Cloud Run, or GKE is a plus.
Experience with merchandising systems, especially Space Planning or Assortment Planning, is a plus.

Responsibilities

Ensure assigned sites, services, applications, and systems continuously and consistently run smoothly, efficiently, and reliably.
Analyze technical situations and make decisions within the assigned subsystem or functional area.
Provide solid problem solving for application issues, production support needs, defects, performance concerns, and operational risks.
Collaborate with development teams to create, support, and continuously improve Python-based solutions while understanding Java/J2EE applications well enough to assist with planning, testing, staging, deployment, and post-release support.
Develop and maintain features, automation scripts, ETL/data workflows, operational jobs, Infrastructure as Code routines, AWX-enabled runbooks, and self-service or self-healing processes for assigned applications and systems.
Apply Linux/Unix administration skills to automate recurring operational tasks, support scheduled processes, review logs, validate permissions, troubleshoot server and job failures, and coordinate production stability activities with infrastructure teams.
Identify and implement code, configuration, Infrastructure as Code, automation, and ETL improvements that improve reliability, performance, repeatability, and supportability.
Support monitoring, alerting, and operational visibility so problems are identified and resolved quickly.
Use CI/CD, source control, JIRA, Agility, or similar tools to maintain accurate task status, support delivery tracking, and manage assigned work.
Participate in product team scrums, refinement sessions, planning discussions, and implementation reviews.
Gather and clarify business or technical requirements for assigned work and translate them into practical engineering tasks.
Work with business partners and other technical teams to explain issues, options, risks, and planned resolution steps in clear language.
Manage own tasks, goals, and training/development while contributing to team delivery commitments.
Look forward 3–9 months within the assigned domain to identify upcoming dependencies, support needs, automation opportunities, ETL/data needs, or technical risks.
Guide newer AutoZoners, interns, or less experienced team members when appropriate by sharing technical knowledge and established practices.
Recommend tools, automation opportunities, AI-assisted practices, and engineering improvements that can help the team work more efficiently.