Senior Data Engineer: Build Scalable Data Pipelines & Lakes

Walmart; Denver (CO); On-site; USD 99,000 - 198,000; Full time

Benefits offered by this job

Health benefits

Live Better U education benefit

401(k) with company match

Stock purchase plans

Paid time off

Job summary

Walmart is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines and architectures that empower business analytics and machine learning initiatives. You will work across teams to translate complex requirements into robust data solutions, ensuring data quality and accessibility in cloud environments.

Responsibilities include building ETL processes, implementing data governance, and leveraging PySpark, SparkSQL, SQL, Python, and Airflow to deliver scalable data

Qualifications

• Bachelor’s degree in CS and 3 years' software engineering or related field.
• 5 years’ experience in software engineering or related field.
• 2 years' experience in data engineering, database engineering, BI, or analytics.
• Experience with data governance, data quality standards, and regulatory compliance.
• Proficiency with cloud services (AWS/GCP) and big data platforms.

Responsibilities

• Design, develop, and maintain scalable data pipelines and architectures.
• Extract, transform, and integrate data from diverse sources with quality.
• Collaborate with stakeholders to translate requirements into data solutions.
• Develop and optimize data models for accessibility and usability.
• Implement data governance and monitor data quality across systems.
• Utilize SQL, Python, Spark, and Airflow for coding, testing, and deployment.
• Monitor and improve data processes to support innovation and operations.

Skills

PySpark

SQL

Python

Java

AWS

GCP

ETL

Apache Airflow

Databricks

Snowflake

Data governance

Education

Bachelor’s degree in Computer Science

Master’s degree in Computer Science

Tools

Terraform

Apache Airflow

Databricks

Snowflake

Job description

Walmart is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines and architectures that empower business analytics and machine learning initiatives. You will work across teams to translate complex requirements into robust data solutions, ensuring data quality and accessibility in cloud environments.

Responsibilities include building ETL processes, implementing data governance, and leveraging PySpark, SparkSQL, SQL, Python, and Airflow to deliver scalable data