(IND) STAFF, DATA ENGINEER
Walmart Inc. (company site, opens in a new tab)12+ yrsBengaluruOn-siteDirect career pageEst. 40–70 LPA
Posted 14h ago
Reach people at Walmart Inc.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Walmart Inc. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own and build scalable, production-grade data pipelines, data models, and data platform architecture supporting Walmart's AI, analytics, and decision-making across business units.
- Lead semantic and dimensional data modeling efforts including development and governance of data standards, certified metrics, and semantic layers for BI and AI use cases.
- Review and guide engineering teams' design and code, implement data governance, quality, and observability measures, while influencing cross-functional data architecture and platform decisions.
Minimum Requirements
- 12+ years professional data engineering experience or equivalent impact.
- Expertise in semantic and dimensional data modeling including conformed dimensions, fact tables, SCD Type 1/2, and snapshots.
- Hands-on experience with Python, SQL, Apache Spark, Hive, Scala, cloud platforms (Azure, Google BigQuery), orchestration tools (Airflow, Dagster), and real-time streaming (Apache Kafka).
- Bachelor's degree in Computer Science with 4+ years software engineering experience, or Master's with 2+ years, plus 3 years in data engineering, DB engineering, BI or analytics.
Ideal Candidate Profile
- Senior individual contributor comfortable making architectural decisions and leading technical initiatives without formal management authority.
- Experienced in building governed, scalable data solutions with strong focus on semantic modeling and enterprise data architecture at large scale.
- Capable of translating complex business needs into data-driven strategies and collaborating with diverse stakeholders across technical and business teams.