Prannay Khushalani

Data Engineer

Talent

Palo Alto, CAMember since May 26, 2026

ScalaPythonSQLPySparkHadoopHDFSMapReduceHiveSqoopdbtGreat ExpectationsApplied Machine LearningLangChainXGBoostSHAP

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ScalaPythonSQLPySparkHadoop

About

Engineered a greenfield retail data platform from 0 to 1, developing high-volume ingestion pipelines using Scala and Spark to process millions of raw user behavioral records into structured, analytics-ready tables. Architected "pre-machine learning" data foundations by building robust ETL workflows that deliver clean, feature-ready datasets for retail predictive modeling and customer signaling teams. Optimized large-scale batch processing jobs in the Hadoop ecosystem, implementing broadcast joins and custom partitioning to reduce processing latency for multi-terabyte retail transaction datasets.

Experience

Data Engineer - Albertsons Companies

(2023-12 - 2026-03)

Engineered a greenfield retail data platform from 0 to 1, developing high-volume ingestion pipelines using Scala and Spark to process millions of raw user behavioral records into structured, analytics-ready tables.
Architected "pre-machine learning" data foundations by building robust ETL workflows that deliver clean, feature-ready datasets for retail predictive modeling and customer signaling teams.
Optimized large-scale batch processing jobs in the Hadoop ecosystem, implementing broadcast joins and custom partitioning to reduce processing latency for multi-terabyte retail transaction datasets.
Developed standardized, granular financial datasets for downstream reporting and AOP planning, utilizing SQL and PySpark to unify data across disparate retail verticals and ensure metric consistency.
Deployed a production-grade LLM-powered monitoring system using LangChain, automating the triage of pipeline failures and reducing mean time to resolution (MTTR) by 70%.
Integrated automated data quality gates using Great Expectations, enforcing schema conformance and validation checks at every stage of the retail data lifecycle to ensure high-fidelity reporting.