Madhuri Kota
Data Engineer @American Technology Consulting Company L.L.C
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WORK HISTORY
Data Engineer @American Technology Consulting Company L.L.C
US
Rebuilt error handling and retry logic for Airflow ETL pipelines on AWS Glue, reducing pipeline failures by 30% and eliminating missed data incidents for business stakeholders. • Redesigned Snowflake and Redshift data models to support SCD Type 1 & 2 transformations, improving query performance by 25% and significantly cutting report generation times. • Built dbt Core transformation models in Snowflake from scratch, collaborating with the analytics team to establish naming conventions and testing standards, reducing manual SQL workload. • Integrated multiple REST APIs and JSON/XML data sources into cloud pipelines, enabling near real-time data delivery to Snowflake and Redshift instead of daily batch loads. • Implemented Great Expectations data quality checks across key pipeline stages, proactively catching data issues before they reached production dashboards. • Introduced CI/CD workflows using GitHub Actions and Docker, accelerating deployment cycles and standardizing the development environment across the team.
EDUCATION
Malineni Lakshmaiah Women’s Engineering College
Bachelor's degree
Lindsey Wilson University
Master of Science, Computer Science
Lindsey Wilson College
Master's degree, Computer Science
Malineni Lakshmaiah Institute of Engineering & Technology
Bachelor of Technology, Electrical, Electronics and Communications Engineering
ABOUT MADHURI KOTA
Most data pipelines look good on paper… until something breaks in production.I’m a Data Engineer who enjoys solving that exact problem — building data systems that are not just scalable, but reliable and easy for teams to trust.Over the past 5+ years, I’ve worked on designing and improving data pipelines in AWS-heavy environments, handling everything from ingestion to transformation to data quality. I’ve worked with tools like PySpark, Airflow, Snowflake, and dbt to turn raw data into something that teams can actually use for decisions.In my current role, I’ve been able to:• Reduce pipeline failures by 30% by improving Airflow reliability • Improve query performance by 25% through better data modeling • Build dbt models that made analytics workflows more consistent • Move pipelines closer to real-time instead of batch processing I’ve also worked on cloud migrations, streaming pipelines with Kafka, and building data quality checks so issues are caught before they impact reports.What I enjoy most about this work is making data simpler and more dependable for others — whether that’s analysts, product teams, or business stakeholders.Tech I work with regularly: AWS, Snowflake, PySpark, Airflow, dbt, Kafka Right now, I’m open to Senior Data Engineer or Cloud Data Engineer roles in the US. Open to roles: Senior Data Engineer | Data Engineer Location: Open to US Opportunities Let’s connect and build data-driven solutions!
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