Data Engineer III - Sunnyvale, CA

As a Data Engineer III at Walmart Global Tech, your primary responsibilities will include data transformation and integration, crafting robust data models, and ensuring the seamless flow of data from diverse sources. You'll also engage in close collaboration with stakeholders and implement data governance practices to maintain data quality, making your role crucial to the organization’s data strategy.

To qualify for the Data Engineer III position at Walmart Global Tech, candidates should have a high-level proficiency in Java and Spring Boot and experience in at least one programming language, which could include Scala or Python. Familiarity with cloud computing platforms, data modeling, and containerization technologies is also essential, along with strong communication skills.

The Data Engineer III role at Walmart Global Tech plays a vital part in translating business requirements into actionable data integration projects, allowing the organization to leverage data effectively for strategic decision-making. By developing efficient data pipelines and ensuring high data quality, you will directly impact business performance and drive innovation.

A Data Engineer III at Walmart Global Tech should be familiar with Java, Spring Boot, cloud platforms like GCP or Azure, and integration tools such as Automic or Airflow. Knowledge of containerization technologies (like Docker and Kubernetes), as well as data warehousing and BI tools, is also advantageous for this role.

In the Data Engineer III role at Walmart Global Tech, you can expect to work collaboratively with cross-functional teams, including business stakeholders and other tech professionals. You'll engage in discussions to understand data needs, contribute to solution recommendations, and help educate team members about data governance and best practices, fostering a collaborative environment.

In answering this question, discuss specific projects you've worked on that involved data transformation, highlighting the tools and methodologies you used. Detail how you ensured data quality and streamlined integration processes, and mention any frameworks or cloud platforms you utilized.

When addressing this question, provide examples of how you've implemented data governance practices in previous roles. Discuss the steps you took to maintain data quality, such as establishing quality checks, stakeholder education, and creating documentation to ensure data integrity.

Be specific about the programming languages you’re experienced with, such as Java, Python, or Scala. Share examples of how you've applied these languages in developing data models or pipelines, including any challenges you faced and how you overcame them.

In your answer, recount an experience where you collaborated with stakeholders to gather requirements for a data project. Highlight your communication skills, how you translated those requirements into actionable tasks, and the successful outcomes that followed.

Discuss specific projects where you utilized GCP or Azure, focusing on the services you employed and the benefits those platforms brought to your data engineering tasks. Emphasize your ability to manage cloud resources effectively.

Talk about the design principles you adhere to when creating data solutions, such as modularity and the use of efficient algorithms. Mention specific tools or technologies you have used to build scalable architectures, like Deltashare or Databricks.

You should outline the techniques you use for data modeling, such as dimensional modeling or entity-relationship diagrams. Explain how these methods help in building data models that are aligned with business objectives and enhance data analysis.

In your response, describe a specific project where you designed an ETL process, detailing the steps involved from extraction to loading the data. Highlight the technologies and best practices you used to ensure the process was efficient and reliable.

Discuss your approach to staying informed about industry trends in data engineering and analytics. This could include participating in relevant online communities, attending workshops, or following industry leaders on social media.

Explain how you create documentation for your projects, including workflows, data models, and governance practices. Mention tools you use for documentation and how you encourage team collaboration and knowledge transfer to ensure everyone is aligned.