Case Study: Unified Data Platform (UDP) Big Data Infrastructure
An enterprise big data ecosystem engineered for Walmart, abstracting infrastructure complexities via YAML-driven and low-code ETL pipelines running on Apache Beam, Spark, and managed Apache Airflow.
The Problem
Building enterprise-grade big data pipelines manually forced engineering teams to manage fragmented data infrastructure, complex scheduling systems, and custom database connectors. This lack of standardization slowed down development velocity, increased production vulnerabilities, and obscured execution visibility.
Engineering Features & Direct Impact
Low-Code Ingestion Engine: Integrates diverse database protocols, Kafka data streams, RESTful APIs, and flat-file assets into an abstracted ingestion layer, allowing self-service pipeline creation via declarative YAML workflows.
Orchestrated Job Telemetry: Embeds fault-tolerant Notebook and workflow APIs directly into managed Apache Airflow instances, exposing deep, real-time metrics on executing Apache Beam and Spark big data jobs.
Automated Validation Framework: Executes automated, end-to-end integration tests for high-volume ETL use cases, significantly cutting down manual validation cycles while maintaining system accuracy.
Hardened Security & CI/CD Pipelines: Embeds SonarQube quality gates directly inside automated deployment pipelines, completely eliminating P1 severity bugs and reducing OWASP web vulnerabilities across codebases.
Rigorous Coverage Optimization: Drives test suite engineering across multiple backend source repositories, expanding overall test code coverage from an unstable 10% up to an enterprise-grade 80%.
Agile Engineering Leadership: Directs cross-functional sprint execution pipelines under strict production SLA metrics, guaranteeing zero operational escalations during critical system upgrades.
The Bottom Line
The System: Delivered a centralized, secure data orchestration ecosystem capable of processing massive enterprise data volumes through standardized Spark and Airflow templates.
The Business: Shifted engineering teams away from manual data infrastructure management, accelerating time-to-production while raising code coverage to 80%.
Technical Stack
Java8
Spring Boot
ReactJs
Apache Kafka
Apache Beam
Apache Spark
Link
Walmart Inhouse Product