Staff Data Engineer

Walmart

. Design, build, and operate large-scale batch and streaming data pipelines using Spark, Java, and Python .

Posted 10/15/2026full-timeBangalore • IndiaLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and operating large-scale data pipelines using Spark, Java, and Python, while ensuring data quality, observability, and governance. Proficient in integrating AI technologies and MLOps practices to enhance data processing and model serving.

Highest-signal resume keywords

Java ProficiencyPython ProficiencySpark ExpertiseData Engineering ExperienceMLOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignDistributed SystemsETL/ELT Pipeline DesignData Quality and ObservabilityBatch and Streaming ProcessingData GovernanceMicroservicesAPI DesignWorkflow OrchestrationDomain-Oriented Design

Soft Skills

Ownership MindsetTechnical JudgmentAutonomy

Tools & Technologies

Hadoop/HDFSHiveKafkaAirflowKubernetesCI/CDCloud-Native Practices

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Computer Science

Industry Keywords

Big DataAIGenAIData TransformationLakehouse Architectures

Tech Stack

Tools & technologies

AirflowCloudDistributed SystemsETLHadoopHDFSJavaKafkaKubernetesMicroservicesPythonSpark

About the role

Key responsibilities & impact

Design, build, and operate large-scale batch and streaming data pipelines using Spark, Java, and Python
Apply software engineering fundamentals including clean architecture, automated testing, CI/CD, and code review
Apply domain-oriented design, system design, and low-level design to data and platform problems
Build and maintain services, APIs, and distributed systems supporting data pipelines
Integrate AI, GenAI, embeddings/vector search, LLM-assisted data quality, anomaly detection, agentic monitoring, self-healing, schema, and lineage documentation into the data platform
Partner with data scientists and ML engineers on feature pipelines, model-serving data paths, and MLOps infrastructure
Own data quality, observability, and governance for pipelines and datasets
Participate in and lead architecture and design reviews
Set technical direction and best practices, mentor engineers, and influence data engineering standards
Evaluate and adopt emerging Big Data, cloud, and AI/agentic technologies

Requirements

What you’ll need

8+ years of professional software engineering experience with significant hands-on data engineering at scale
Strong proficiency in Java and Python
Strong working knowledge of Spark for distributed data processing
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
Operational Excellence and Engineering Excellence skills, including SLO/SLA ownership, incident management, blameless post-incident reviews, reliability and quality metrics, and continuous improvement
Deep experience with Spark, Hadoop/HDFS, Hive, Kafka, workflow orchestration such as Airflow, batch and streaming processing, and large-scale data transformation
Experience with data modeling, ETL/ELT pipeline design, data quality and observability, data governance, and lakehouse architectures
Hands-on experience integrating model APIs and GenAI/LLM tooling, building or operating agentic workflows, embeddings/vector search, and MLOps practices
Working literacy in microservices, API design, Kubernetes or equivalent orchestration, CI/CD, and cloud-native practices
Strong distributed systems, event-driven patterns, service contracts, asynchronous processing, fault tolerance, domain-oriented design, system design, and low-level design skills
Strong software engineering craftsmanship, including testing strategy, code review standards, and design patterns
Ability to translate ambiguous data/business problems into technical execution plans
Strong ownership mindset and technical judgment; comfortable operating with high autonomy
Minimum qualifications include either: Bachelor's degree in Computer Science and 4 years' experience in software engineering or related field; 6 years' experience in software engineering or related field; or Master's degree in Computer Science and 2 years' experience in software engineering or related field
3 years' experience in data engineering, database engineering, business intelligence, or business analytics

Benefits

Comp & perks

Incentive awards for performance
Maternity and parental leave
PTO
Health benefits
Flexibility for associates to manage their personal lives