Staff Data Engineer: Real-Time Platforms & AI Enablement

Walmart; Sunnyvale (CA); On-site; USD 143,000 - 286,000; Full time

Benefits offered by this job

Health benefits

401(k) plan

Stock purchase plan

Paid time off

Life insurance

Job summary

Walmart in Sunnyvale, CA is seeking a Staff Data Engineer to shape data platforms and pipelines that power membership, analytics, and customer growth. You will lead architecture at petabyte scale and mentor engineers across teams.

You’ll own data platform engineering, analytics enablement, and engineering excellence, partnering with data scientists and product teams to operationalize ML and AI while ensuring quality, governance, and cost efficiency.

Qualifications

• Bachelor’s degree in Computer Science with 4+ years software engineering experience.
• 6+ years of software engineering experience.
• Master’s degree in Computer Science with 2+ years experience.
• 3 years of experience in data engineering, database engineering, BI, or analytics.

Responsibilities

• Own architecture for large-scale streaming data.
• Design, build, and maintain scalable data pipelines for batch and real-time workloads.
• Develop ingestion, transformation, and orchestration frameworks for structured and unstructured data.
• Ensure data quality, reliability, observability, and governance.
• Build self-service platform capabilities to improve developer productivity.
• Improve platform reliability through observability, alerting, and automated remediation.

Skills

Python

Java/Scala

Airflow

GCP/BigQuery

Spark/Flink/Beam

Data modeling

CI/CD

Distributed systems

Data governance

Education

Bachelor’s degree in Computer Science

Master’s degree in Computer Science

Tools

Airflow

BigQuery

Hive

Presto

GCP

Job description

Walmart in Sunnyvale, CA is seeking a Staff Data Engineer to shape data platforms and pipelines that power membership, analytics, and customer growth. You will lead architecture at petabyte scale and mentor engineers across teams.

You’ll own data platform engineering, analytics enablement, and engineering excellence, partnering with data scientists and product teams to operationalize ML and AI while ensuring quality, governance, and cost efficiency.