Data Platform Engineer - Senior Systems Engineer

Job Description

About AutoZone:

AutoZone is the nation's leading retailer and a leading distributor of automotive replacement parts and accessories with more than 6,000 stores in US, Puerto Rico, Mexico, and Brazil.

Each store carries an extensive line for cars, sport utility vehicles, vans and light trucks, including new and remanufactured hard parts, maintenance items and accessories.

We also sell automotive diagnostic and repair software through ALLDATA, diagnostic and repair information through ALLDATAdiy.com, automotive accessories through AutoAnything.com and auto and light truck parts and accessories through AutoZone.com.

Since opening its first store in Forrest City, Ark.

on July 4, 1979, the company has joined the New York Stock Exchange (NYSE: AZO) and earned a spot in the Fortune 500.

AutoZone has been committed to providing the best parts, prices, and customer service in the automotive aftermarket industry.

We have a rich culture and history of going the Extra Mile for our customers and our community.

At AutoZone you're not just doing a job; you're playing a crucial role in creating a better experience for our customers, while creating opportunities to DRIVE YOUR CAREER almost anywhere! We are looking for talented people who are customer focused, enjoy helping others and have the DRIVE to excel in a fast-paced environment!

Position Summary

The Senior Data Engineer is a technical expert responsible for designing, implementing, and supporting scalable data solutions using modern big data technologies.

In this full-time role, you will work closely with data architects, analysts, and business stakeholders to build, optimize, and maintain data pipelines and platforms that drive analytics, reporting, and machine learning.

You will ensure the reliability, performance, and security of production data systems, and play a key role in troubleshooting, monitoring, and continuous improvement.

Responsibilities



* Design, develop, and maintain robust data pipelines for ingesting, transforming, and storing large volumes of structured, semi-structured, and unstructured data.


* Implement data workflows and ETL processes using technologies such as Spark, Delta Lake, and cloud-native tools.


* Support the production use of big data platforms (e.g., Databricks, Snowflake, Google Cloud Platform), ensuring high availability, scalability, and performance.


* Monitor, troubleshoot, and resolve issues in production data systems, including job failures, performance bottlenecks, and data quality concerns.


* Collaborate with data architects to translate business requirements into technical solutions, ensuring alignment with architectural standards and best practices.


* Optimize SQL queries, Spark jobs, and data processing workloads for efficiency and cost-effectiveness.


* Implement and maintain data governance, security, and compliance measures, including access controls, data masking, and audit logging.


* Integrat...