Lead Data Engineer

Job Description

WHO WE ARE  

Come join our Technology Team and start reimagining the future of the automotive aftermarket. We are a highly motivated tech-focused organization, excited to be amid dynamic innovation and transformational change. Driven by Advance’s top-down commitment to empowering our team members, we are focused on delighting our Customers with Care and Speed, through delivery of world class technology solutions and products.   

We value and cultivate our culture by seeking to always be collaborative, intellectually curious, fun, open, and diverse.   You will be a key member of a growing and passionate group focused on collaborating across business and technology resources to drive forward key programs and projects building enterprise capabilities across Advance Auto Parts.   

THE OPPORTUNITY: 

Join the AAP team and start reimagining the future of automotive retail. Disrupt the way consumers buy auto parts and take on the industry’s biggest challengers to execute on AAP's top-down commitment to digital expansion.  

As a member of the Advance Auto Parts team, you will have an opportunity to disrupt a $150B auto parts industry to bring better and faster solutions to customers. You will be part of a team helping the company live its mission of “Advancing a World in Motion”. The role is part of a merit-based organization with a culture of professional growth and development, and emphasis on the latest tools, platforms and technologies.  

Responsibilities: 

Lead the migration and modernization of data platforms, moving applications and pipelines to Google Cloud-based solutions. 

Architect and maintain cloud-based data infrastructure leveraging AWS or GCP services. 

Ensure data security and governance, enforcing compliance with industry standards and regulations. 

Develop and promote best practices for data modeling, processing, and analytics. Mentor and guide a team of data engineers, fostering a culture of innovation and technical excellence. 

Manage and scale data pipelines from internal and external data sources to support new product launches and ensure high data quality. 

Develop automation and monitoring frameworks to capture key metrics and operational KPIs for pipeline performance. 

Collaborate with internal teams, including data science and product teams, to drive solutioning and proof-of-concept (PoC) discussions. 

Develop and optimize procedures to transition data into production. 

Define and manage SLAs for data products and operational processes. 

Research and apply state-of-the-art methodologies in data and Platform engineering. 

Create and maintain technical documentation for sharing knowledge. 

Develop reusable packages and libraries to enhance development efficiency. 

Lead and drive the development and optimization of scalable data architectures and pipelines. 

Develop real-time and batch data processing solutions, integrating structured and unstructured data sources. 

Required Qualification: 

• We are looking for a candidate with 10+ years of experience in Data Engineering and Application development with at least 3+ years in a Technical Lead role. They must have a graduate degree in Computer Science or a related field of study. They must have experience with programming languages such as Python, Java & DS&Algo, Spark, and Scala. Expertise in Python and Spark is a must. 

• 4 + years of AWS and Cloud technologies. Experience in data platform engineering, with a focus on cloud transformation and modernization. 

• Hands-on experience building large, scaled data pipelines in cloud environments and handling of data in PBs. 

• Experience with CI/CD pipeline management in GCP DevOps. 

• Understanding of data governance, security, and compliance best practices. 

• Experience working in an Agile development environment. 

• Prior experience in migrating applications from legacy platforms to the cloud. 

• Knowledge of Terraform or Infrastructure-as-Code (IaC) for cloud resource management. 

• Familiarity with Kafka, Event Hubs, or other real-time data streaming solutions. 

• Experience with legacy RDBMS (Oracle, DB2, Teradata) & DataStage/Talend 

• Having background supporting data science models in production.  

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