Meghana Polisetty
Sr Data Analyst @Walmart
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WORK HISTORY
Sr Data Analyst @Walmart
US
Architected and optimized BigQuery data pipelines, implementing partitioning, clustering, and query tuning strategies that reduced compute costs, improved throughput, and supported large-scale analytics, driving multi-million dollar savings- Developed a GCP-based SQL capacity planning engine, integrating forecast, transportation, and financial data marts; eliminated purchase transportation inefficiencies and automated scenario planning for enterprise-wide cost optimization- Redesigned ETL workflows in BigQuery + Dataiku & Alteryx, leveraging parameterized recipes, dependency management, and incremental loading to cut data latency by 80% and reduce batch runtime from 3 hours → 30 minutes- Built executive-grade Tableau dashboards directly on optimized SQL models, incorporating window functions, LODs, and CTE-driven joins, increasing reporting accuracy by 15% and reducing dashboard refresh times by 30%- Partnered with Finance & Ops Engineering to deploy SQL-driven budget and spend-tracking data models, introducing automated variance checks, anomaly detection, and cost attribution logic that lowered non-essential route expenses by 12%.
EDUCATION
SRM University
Bachelor of Technology - BTech
San Jose State University
Master of Science - MS
ABOUT MEGHANA POLISETTY
Senior Data Engineer building and owning production-grade analytics data products and metrics layers that leadership trusts to run Marketplace businesses.I currently work in Walmart Marketplace, where I own end-to-end measurement systems that track seller adoption, engagement, and retention across dozens of Marketplace programs. My work focuses on building durable source-of-truth datasets, protecting KPI integrity through constant product change, and shipping launch-ready metrics at scale.What I do• Own foundational analytics datasets and metrics layers used in WBRs and executive reporting• Build scalable pipelines across Spark, Hive/Parquet, Trino/Presto, and BigQuery, integrating event telemetry, seller attributes, Salesforce cases, SLA milestones, surveys, and inventory data• Anticipate and mitigate KPI risk during UI, taxonomy, and product launches using forward-only cutovers, event allowlists, gating filters, and historical validation• Lead large-scale migrations and backfills with zero reporting disruption• Debug data correctness issues across identity definitions, timezones, latency, and missing record types• Ship all changes via PR-driven engineering workflows with validation, documentation, and cross-functional sign-offHow I workEngineering-first: partitioned and incremental models, cost/perf optimization, validation frameworks, reliable refresh behaviorMetrics-focused: KPI definition governance, reconciliation across sources, finance-aligned semanticsProduct-minded: close partnership with Product, Analytics, and Engineering to ensure metrics are decision-safe and launch-readyBackgroundMy experience spans Marketplace Analytics, FinTech SaaS, and Supply Chain/Operations, with a consistent theme: building data systems that reduce risk, improve efficiency, and drive measurable business outcomes.TechSpark / PySpark · Hive · Trino / Presto · BigQuery · SQL · Git/GitHub · Mixpanel · Salesforce · Data Modeling · Metrics Layers · Data Quality · Production ETLOpen to Senior Data Engineer, Analytics Engineer, or Product Data roles where owning core metrics and production data systems matters.
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