Sr. Principal Engineer, Data (Multiple Positions)

CarMax•Richmond, VA

6d•Onsite

About The Position

CarMax, the way your career should be! Summary of Duties: Serve as a key individual contributor in the design, development, and optimization of our Enterprise Data Warehouse (EDW), Data Lake, and Lakehouse platforms. Independently design and implement scalable and efficient data architectures for Enterprise Data Warehouse (EDW), Data Lake, and Lakehouse solutions with a strong focus on performance, scalability, and cost optimization. Architect robust data pipelines, integrating data across various sources and ensuring smooth data flow into Snowflake, Teradata, and other platforms. Drive data integration strategies across structured, semi-structured, and unstructured data sources using Azure, Snowflake, Hadoop, Spark, and other relevant tools. Develop, maintain, and optimize high- performance data pipelines, leveraging cloud technologies such as Azure, Snowflake, and Big Data frameworks to process large datasets efficiently. Continuously optimize data ingestion, transformation, and storage pipelines for enhanced performance, ensuring they are scalable, cost-effective, and adhere to organizational SLAs. Write efficient Python code for automating data workflows and integrating various data sources. Apply advanced performance optimization techniques to improve query execution times and reduce resource consumption, focusing on query tuning, indexing, partitioning, and caching strategies. Optimize data queries within Snowflake and Teradata to ensure they are processed in the most efficient way possible, minimizing compute costs and time. Troubleshoot and resolve complex performance issues within large-scale distributed data systems. Collaborate closely with business and strategy teams to understand data requirements and ensure that the data architecture aligns with business objectives. Provide data engineering expertise in meetings with stakeholders, translating business needs into actionable data solutions and identifying opportunities for optimization. Work with data scientists, analysts, and other engineers to ensure that data pipelines meet the needs of analytical and reporting use cases. Mentor junior data engineers by providing guidance on best practices, helping them solve complex technical challenges, and assisting in their professional development. Stay up to date with the latest trends and technologies in data engineering, big data, cloud computing, and performance optimization. Evaluate and integrate new tools, techniques, and technologies into the existing data infrastructure to drive continuous improvement and innovation. About CarMax CarMax disrupted the auto industry by delivering the honest, transparent and high-integrity experience customers want and deserve. This innovative thinking around the way cars are bought and sold has helped us become the nation’s largest retailer of used cars, with over 200 locations nationwide. Our amazing team of more than 25,000 associates work together to deliver iconic customer experiences. Along the way, we help every associate grow their career and achieve their best, at work and in their community. We are recognized for our commitment to training and diversity and are one of the FORTUNE 100 Best Companies to Work For®. CarMax is an equal opportunity employer, and all qualified candidates will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, protected veteran status, disability status, or any other characteristic protected by law. Upon an applicant's request, CarMax will consider reasonable accommodation to complete the CarMax Job Application .

Requirements

Bachelor’s degree in Information Systems, Information Technology, Computer Science, Operations (any), Management (any), Engineering (any), Analytics (any), Business (any), Language (any), Telecom, Math, Physics, Electrical/Electronics, or a related field of study, AND Eight (8) years of experience in the job offered or related occupation in which the required experience was gained.
In lieu of a Bachelor’s degree in Information Systems, Information Technology, Computer Science, Operations (any), Management (any), Engineering (any), Analytics (any), Business (any), Language (any), Telecom, Math, Physics, Electrical/Electronics, or a related field of study, AND Eight (8) years of experience, the employer will also accept a Master’s degree in Information Systems, Information Technology, Computer Science, Operations (any), Management (any), Engineering (any), Analytics (any), Business (any), Language (any), Telecom, Math, Physics, Electrical/Electronics, or a related field of study, AND Six (6) years of experience in the job offered or related occupation in which the required experience was gained.
Must also have demonstrated experience with the following:
Building and optimizing data platforms at scale
Azure, Snowflake, Teradata, Hadoop, Spark, and other Big Data technologies
Data pipeline development, data integration, data quality and optimization in cloud environments
Cloud-based computer architecture, Snowflake, and Teradata architecture
Performance tuning, query optimization, and cost management, particularly in Snowflake and Teradata
Using Python for automation, data transformations, and workflow management
Advanced SQL skills for complex query writing and optimization in large-scale data environments.

Responsibilities

Serve as a key individual contributor in the design, development, and optimization of our Enterprise Data Warehouse (EDW), Data Lake, and Lakehouse platforms.
Independently design and implement scalable and efficient data architectures for Enterprise Data Warehouse (EDW), Data Lake, and Lakehouse solutions with a strong focus on performance, scalability, and cost optimization.
Architect robust data pipelines, integrating data across various sources and ensuring smooth data flow into Snowflake, Teradata, and other platforms.
Drive data integration strategies across structured, semi-structured, and unstructured data sources using Azure, Snowflake, Hadoop, Spark, and other relevant tools.
Develop, maintain, and optimize high- performance data pipelines, leveraging cloud technologies such as Azure, Snowflake, and Big Data frameworks to process large datasets efficiently.
Continuously optimize data ingestion, transformation, and storage pipelines for enhanced performance, ensuring they are scalable, cost-effective, and adhere to organizational SLAs.
Write efficient Python code for automating data workflows and integrating various data sources.
Apply advanced performance optimization techniques to improve query execution times and reduce resource consumption, focusing on query tuning, indexing, partitioning, and caching strategies.
Optimize data queries within Snowflake and Teradata to ensure they are processed in the most efficient way possible, minimizing compute costs and time.
Troubleshoot and resolve complex performance issues within large-scale distributed data systems.
Collaborate closely with business and strategy teams to understand data requirements and ensure that the data architecture aligns with business objectives.
Provide data engineering expertise in meetings with stakeholders, translating business needs into actionable data solutions and identifying opportunities for optimization.
Work with data scientists, analysts, and other engineers to ensure that data pipelines meet the needs of analytical and reporting use cases.
Mentor junior data engineers by providing guidance on best practices, helping them solve complex technical challenges, and assisting in their professional development.
Stay up to date with the latest trends and technologies in data engineering, big data, cloud computing, and performance optimization. Evaluate and integrate new tools, techniques, and technologies into the existing data infrastructure to drive continuous improvement and innovation.