WHO WE ARE
Come join our diverse Advance AI Team and start reimagining the future of the automotive aftermarket. We are a highly motivated, tech-focused organization, excited to be in the midst of 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. As a Data Engineer within the Advance AI team, 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 data & analytics capabilities across Advance Auto Parts.
This position is remote and candidates will be considered from any US city.
THE OPPORTUNITY
As the Principal Data Engineer, you will be hands-on using AWS, SQL and Python daily with a team of Software, Data and DevOps Engineers. This position has access to massive amounts of customer data and will be responsible for the end-to-end management of data from various sources.You will work with structured and unstructured data to solve complex problems in the aftermarket auto care industry.
ESSENTIAL DUTIES AND RESPONSIBILITIES include the following; other duties may be assigned:
ENGINEER
Build processes supporting data transformation, data structures, metadata management, dependency, and workload management.
Implement cloud services such as AWS EMR, EC2, EMR, Snowflake, Elastic-Search, Juypter notebooks
Develop stream-processing systems: Storm, Spark-Streaming, Kafka etc
Deploy data pipeline and workflow management tools: Azkaban, Luigi, Airflow, Jenkins
Scale and deploy AI products for customer facing application impacting millions of end-users using Openshift on hybrid cloud.
Develop the architecture for deploying AI products that can scale and meet enterprise security and SLA standards
Develop, construct, test, and maintain optimal data architectures.
Identify, design, and implement internal process improvements such as automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
Perform hardware provisioning, forecasting hardware usage, and managing to a budget
Perform security standards like symmetric and asymmetric encryption, virtual private clouds, IP management, LDAP authentication, and other methods
LEADERSHIP
Share outcomes through written communication, including an ability to effectively communicate with both business and technical teams
Succinctly communicate timelines, updates and changes to existing & new projects and deliverables in timely fashion
Work with the senior leadership within the organization to develop a long-term technical strategy. Map business goals to appropriate technology investments
Mentor and manage other Data Engineers, ensuring data engineering best practices are being followed
Challenge technical status quo and be comfortable in receiving feedback on your ideas and work
Be a hands-on practitioner and lead by example
QUALIFICATIONS
Be a self-starter, comfortable with ambiguity and enjoy working in a fast-paced dynamic environment
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
Strong analytic skills related to working with unstructured datasets
Experience building and optimizing ‘big data’ data pipelines, architectures and data sets
Experience in cloud services such as AWS EMR, EC2, Juypter notebooks
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and see opportunities for improvement
A successful history of manipulating, processing, and extracting value from large, disconnected datasets
Solid understanding of message queuing, stream processing, and highly scalable ‘big data’ data stores
Strong project management and organizational skills. Knowledge or experience with Agile methodologies is a plus
Experience supporting and working with multi-functional teams in a dynamic environment
Experience using the following software/tools:
Strong experience with AWS cloud services: EC2, EMR, Snowflake, Elastic-Search, Openshift
Experience with stream-processing systems: Storm, Spark-Streaming, Kafka etc.
Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Experience with big data tools: Hadoop, Spark, Kafka, Kubernates etc.
Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
EDUCATION AND EXPERIENCE REQUIREMENTS
Master’s in Computer Science or related field required
8-10+ years of direct experience developing enterprise grade application
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