Associate 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

Advance Auto Parts, a leader in the automotive aftermarket, currently has an opening for Analytics Engineer.  This role seeks a Tag Management experience to facilitate data-driven insights for the organization. You'll implement end-to-end data flows (website > Tealium > Google Analytics > BigQuery > AWS S3 > Snowflake) within a cloud environment, collaborating with development, data engineering, and product teams.

• Building the Foundation: Analytics engineers create the infrastructure to collect, store, and process this vast digital data. They design pipelines to move data between systems, ensuring accessibility, security, and quality.
• Data Warehousing & Modeling: They develop data warehouses and data models tailored for analysis within the digital space (e.g., understanding customer journeys across multiple platforms)
• Working with Analytics Teams: Analytics Engineers partner closely with data analysts and data scientists to provide clean, well-structured data sets that enable meaningful insights.
• Enabling Business Impact: Insights derived from digital data help optimize marketing campaigns, personalize customer experiences, and improve product development – Analytics engineers are the architects making this possible.

Job Summary:

We seek a highly skilled Analytics Engineer to develop our data collection, modeling, and analytics infrastructure. With experience in tag management solutions, workflow orchestration, and a strong foundation in cloud technologies, you will design a robust data ecosystem that empowers business insights and decision-making.

Responsibilities & Duties:

• Develop tag management solutions (Tealium/GTM) ensuring accurate and comprehensive data capture.
• Select and implement ETL tools to streamline data extraction, transformation, and loading processes.
• Build scalable and performant data models on Google Cloud, leveraging Big Query for data warehousing and analysis.
• Collaborate with marketing, analytics, and business teams to understand data requirements and build data solutions that address key business questions.
• Proficiently utilize SQL and scripting languages (JavaScript/HTML) for data extraction, manipulation, and visualization.
• Apply expertise in Google Analytics 4 (GA4) to configure and customize data collection for enhanced insights.
• Experience with Airflow pipelines for seamless data orchestration and processing.
• Stay updated on the latest trends and technologies in data engineering and analytics, bringing innovative ideas to the table.

Qualifications:

• Required:
  • 6+ years of experience in Analytics engineering role.
  • Proven ability to use communication to foster positive relationships and drive project success.
  • Proven ability to design robust data pipelines and architectures that support data-driven decision-making for websites and mobile applications.
  • Experience in tag management solutions (Tealium/GTM) for comprehensive website and app data tracking.
  • Knowledge of Google Cloud, particularly Google Big Query for data warehousing and analysis.
  • Frontend expertise in React, JavaScript, and HTML, along with Python knowledge for backend development.
  • Experience in utilizing Google Analytics 4 (GA4) for advanced data collection and analysis.
  • Experience with ETL tools and understanding of ETL processes - Building/Optimizing ETL processes for AWS.
  • SQL knowledge for advanced analysis and database optimization
• Preferred:
  • Experience in a similar industry (e.g., retail, e-commerce, digital marketing)
  • Experience with Python/PySpark for data processing and analysis.
  • Working knowledge of Snowflake for data warehousing.
  • Experience in Airflow, or similar workflow orchestration tools for managing data pipelines.

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