Open to opportunities

vaishnavi User

@vaishnaviuser3

Message

I am a data engineer specializing in Azure, PySpark, and ETL.

Canada

Message

What I'm looking for

I am seeking a mid-level data engineering role focused on cloud-native Azure pipelines, scalable ETL, CI/CD automation, and delivering analytics that drive business decisions in a collaborative, Agile environment.

I am a data engineer with over two years of experience building cloud-based data solutions on Azure using PySpark, Databricks, and SQL. I focus on designing reliable ETL pipelines and medallion architectures to turn raw data into actionable insights.

I have engineered Azure-based medallion architectures to ingest and transform 10M+ logs, built Spark Structured Streaming pipelines processing 5M+ daily events, and migrated legacy Excel reports into Power BI, reducing load time and improving accuracy. I also developed and deployed a CNN to IBM Cloud achieving 86% accuracy and tuned complex SQL and table structures to substantially reduce query latency.

I work well in cross-functional Agile teams and prioritize performance, automation, and reproducibility—using Azure Data Factory, Synapse, DevOps CI/CD, GitHub Actions, and testing frameworks to deliver scalable data platforms and clear analytics for product and IT stakeholders.

Experience

Work history, roles, and key accomplishments

Current

Data Analyst Intern

Current

Npower Canada

Apr 2025 - Present (4 months)

Built Power BI dashboards and optimized DAX/Power Query to reduce report load time by 67% and migrated legacy Excel reports, improving data accuracy by 30%. Authored complex SQL to analyze 5M+ records/day, reduced query latency 45%, and developed a CNN achieving 86% accuracy for food classification.

Power BI DAX Power Query SQL Python Pandas Azure Data Visualization Machine Learning

Data Engineer

Tata Consultancy Services

May 2021 - Apr 2023 (1 year 11 months)

Engineered an Azure-based medallion architecture to ingest and transform 10M+ chatbot logs, reducing data preparation time by 55% and built Spark Structured Streaming pipelines processing 5M+ ERP interactions/day. Orchestrated workflows with Azure Data Factory and Synapse and implemented CI/CD using GitHub Actions to support real-time and batch analytics.