Vinoth Venkatesan

University of Madras

Master of Computer Applications (MCA)

Sathyabama Institute of Science & Technology

Bachelor of Science (BS)

Computer Technology

SnowPro Advanced: Architect Certification

Snowflake

Microsoft Certified: Fabric Data Engineer Associate

Microsoft

SnowPro Core Certification

Snowflake

Fivetran Technical Certification

Fivetran

Microsoft Certified: Azure Data Fundamentals

Microsoft

Oracle Database 11g: SQL Fundamentals (1Z0-051)

Oracle

Oracle PL/SQL Developer Certified Associate (1Z0-144)

Oracle

SPOT Award

LatentView

Associated with Affirm

R&R Award

LatentView

Associated with Affirm

Data Engineer · The Home Depot

• Architected Snowflake star-schema and event models powering AI-driven analytics across 600+ branches, enabling smarter operational decisions at scale.
• Built a hierarchical compliance rule engine (Matillion + Snowflake) validating 5M+ eCommerce products/day, contributing to $1M+ in digital revenue.
• Delivered a real-time Route Planner using Snowflake delta detection, syncing only modified orders and streamlining logistics operations.
• Built a Snowflake-native observability framework (freshness, volume, schema drift) catching anomalies before nightly ELT runs and boosting data trust.
• Launched a Streamlit + Cortex AI cost-monitoring app with 2-sigma anomaly detection and object-level credit attribution — driving proactive cost savings.

Data Engineer · NerdWallet

• Cut Snowflake compute spend by $15K/month via warehouse right-sizing, workload isolation, and auto-suspend tuning; mentored team to scale practices org-wide.
• Re-architected legacy ETL with Airflow, reducing batch runtime by 80% (8 hrs → 45 min) for faster business insights.
• Tuned Airflow tasks to leverage Spot Instances, saving an additional $2K/month in compute.

Data Engineer · Affirm

• Migrated 55+ LTV modeling pipelines to Snowflake dbt models for Marketing, Growth Analytics & Ops Analytics, enabling trusted attribution insights that drive marketing investment decisions.
• Built dbt models (staging → intermediate → mart) powering the data science team's MMM model, decomposing sales into baseline vs. marketing-driven impact to guide spend.
• Automated marketing reporting via Databricks–Snowflake–Google Sheets with scheduled refreshes, saving business teams 2–4 hours per cycle.
• Built a dedicated Snowflake consumption layer accelerating Tableau-to-Looker Studio migration and cutting dashboard development time.

Hadoop Developer · State Farm

• Engineered Spark (Scala/Python) ETL jobs parsing multi-format event logs (JSON/CSV/text), accelerating downstream analytics.
• Integrated Kafka as the real-time ingestion layer for high-volume distributed event streams into Hadoop, with tuned topics, partitions, and replication for fault tolerance.
• Detected 25+ fraudulent activities via web-log keyword filtering; delivered warehouse solutions improving transaction system performance by 45–65%.

Associate Consultant · British Telecom

• Improved SQL query performance by 70% via strategic indexing and removal of inefficient cursors/temp DB usage.
• Automated quarterly pricing pipelines (staging → dim → fact), eliminating manual effort and ensuring accuracy across all telecom products.

Oracle Developer · Humana

• Tuned 80+ slow SQL queries in SSIS ETL packages using explain plans and Oracle hints, cutting runtime by 60%.
• Identified $1M+ in annual over/underpayments in medical claims through DataMart analysis support.

Product Specialist · IVY CPG

• Built custom SSRS reports improving department workflow by 45%; resolved 30+ production tickets ensuring data accuracy.