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Brundesh R

@brundeshr

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Senior data engineer building scalable real-time data systems and AI agents.

India

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What I'm looking for

I want to build real-time, multi-tenant data platforms that improve freshness and performance, with strong observability and SLA-aware orchestration. I’d also like to combine data engineering with agentic AI systems.

I’m a Senior Data Engineer with 10+ years of experience building large-scale, real-time data systems across retail, telecom, and enterprise domains. I specialize in Apache Kafka, Apache Spark, and GCP-native stacks, with a strong focus on performance, scalability, and operational reliability.

At Walmart Global Tech, I lead data engineering for the In-Stock Assistant (ISA), a multi-tenant inventory intelligence platform serving 4 global markets. I architect multi-source streaming and batch pipelines that ingest real-time store signals, scan events, and inventory feeds to deliver sub-minute freshness for in-stock decision-making.

I’ve consistently driven measurable outcomes—delivering 40–60% performance improvements and consolidating fragmented systems into unified, scalable platforms. I also standardize CI/CD workflows across pipeline components using Concord and Looper, orchestrate dependencies with Apache Airflow, and ensure SLA-aware, observable DAG design for multi-market operations.

Beyond core data engineering, I actively build agentic AI systems using LangGraph and ReAct patterns, bridging data engineering with next-generation AI capabilities. Earlier, I delivered a real-time Track & Trace platform at Jio Platforms and built migration pipelines with privacy controls at Deloitte, while mentoring engineers on Spark optimization and data pipeline best practices.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Walmart Global Tech

Apr 2022 - Present (4 years 3 months)

Leads data engineering for In-Stock Assistant, a multi-tenant inventory intelligence platform processing real-time store signals across multiple markets. Architected Kafka-based ingestion, Spark/Beam transformations, multi-source data fusion, and Airflow orchestration with CI/CD standardization for reliable sub-minute freshness.

Kafka Spark Structured Streaming Google Cloud Dataflow BigQuery Hive PySpark Scala Airflow CI CD Concord Looper Observability SLA Aware DAG Design Apache Spark Data Ingestion

Technical Lead (Senior Developer)

Jio Platforms

Jan 2019 - Jan 2022 (3 years)

Architected and delivered a real-time Track & Trace platform processing GPS and telemetry events for end-to-end logistics and asset visibility. Implemented geo-fencing, reporting frameworks, and anomaly-aware distance calculation to improve tracking reliability and reduce reporting turnaround time.

Real time Data Processing Track And Trace Telemetry Distance Calculations Anomaly Detection Spatial Indexing Mentor

Consultant 4 (Senior Developer)

Deloitte USI

Jan 2018 - Jan 2019 (1 year)

Designed and executed data migration pipelines from Edward EDW to a cloud data lake, ensuring integrity and continuity for downstream analytics. Built Spark Scala transformation/cleansing pipelines and implemented PII data masking to support data privacy compliance.

Data Migration Data Lake Apache Spark Scala Data Masking Data Privacy Compliance Data Pipelines data transformation

Hadoop Consultant

Data Semantics

Jan 2015 - Jan 2018 (3 years)

Developed streaming and batch data ingestion and processing pipelines using Kafka and Spark on Azure. Implemented Presto-based federated analytics and defined Azure Blob Storage partitioning and retention strategies to improve query performance and reduce storage costs.