Walmart U.S. offers an extensive selection that our customers value, whether they shop online at Walmart.com, through one of our mobile apps, or in-store. Focus areas include customers, stores and employees, in-store service, merchant tools, merchant data science, and search and personalization.

What you’ll do:

• Develop, construct, test, and maintain architectures, such as databases and large-scale processing systems.
• Recommend and implement ways to improve data reliability, efficiency, and quality.
• Employ a variety of languages and tools to marry systems together.
• Explore ways to enhance data quality and reliability.
• Collaborate with Engineers, data scientists, analysts, and other team members to understand data needs and implement systems to fulfill these needs.
• Ensure data architecture will support the requirements of business initiatives and data analytics.
• Use data modeling and ETL processes to ensure the integrity of data warehouses.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
• Work with stakeholders, including the Executive, Product, Data, and Design teams, to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data secure across national boundaries through multiple data centers and AWS regions.

What you’ll bring:

• Bachelor’s degree in computer science, or a related field.
• 5+ years of experience in a Data Engineer role, with successful history of manipulating, processing, and extracting value from large, disconnected datasets.
• Advanced working SQL knowledge and experience working with relational databases, as well as working familiarity with a variety of databases.

• Experience building and optimizing data pipelines, architectures, and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
• Strong project management and organizational skills.
• Experience with big data tools: Hadoop, Spark, Kafka, Pyspark etc.
• Experience with data pipeline and workflow management tools: Luigi, Airflow, etc.
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java etc.