✦ Luna Orbit — Data & Analytics

Data Engineer III

at Walmart

📍 Sunnyvale, CA Unknown 💰 $117K – $234K USD / year Posted March 18, 2026
Salary $117K – $234K USD / year
Type Full-Time
Experience mid
Exp. Years 3+ years
Education Not specified
Category Data & Analytics

This role involves designing and maintaining scalable data pipelines and ETL processes to support analytics and reporting. The candidate will collaborate with cross-functional teams to optimize data architecture and ensure data quality.

  • Design data pipelines
  • Develop ETL processes
  • Collaborate with teams
  • Optimize data storage
  • Ensure data quality

The technical environment includes big data technologies such as Apache Spark and Kafka, cloud storage solutions, and data modeling techniques. The role emphasizes data governance and real-time data processing.

The ideal candidate is a mid-level data engineer with at least 3 years of experience in building scalable data pipelines and ETL processes. They should be proficient in SQL, Python, and big data technologies like Apache Spark and Kafka, with a strong understanding of data quality and governance.

Experience in data engineeringProficiency in SQLKnowledge of Apache Spark and KafkaData modelingETL processes
Big data technologiesCloud data storageData privacy and security
Apache SparkApache KafkaCloud platforms
SQLJavaPythonApache SparkApache Kafkadata pipelinesETLdata modelingcloud platformsdata qualitydata governance
SQLJavaPythonApache SparkApache KafkaData pipelinesETL processesData modelingCloud platformsData qualityData governance
CollaborationCommunicationProblem-solvingAnalytical thinkingTeamwork
Industry Retail / E-commerce / Technology
Job Function Building and maintaining scalable data pipelines for analytics
Role Subtype Data & Analytics
Tech Domains Apache Spark, Apache Kafka, SQL / PostgreSQL
data engineerSQLJavaPythonApache SparkApache KafkaETLdata pipelinesdata modelingcloud platformsdata qualitydata governancebig datadata privacydata securityanalyticsreal-time decision makingAIcloud storage

Lack of experience in data engineering, No proficiency in SQL or Python, Unfamiliarity with Apache Spark or Kafka, No knowledge of data governance or data quality

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