Pranav Naidu

About Pranav Naidu

As a Data Engineer with over 4 years of experience, I specialize in architecting and developing large-scale, cloud-native data platforms and intelligent analytics solutions. I have a strong background in building secure, scalable data pipelines and AI-driven systems using Snowflake, Azure, Databricks, Python, and Informatica IICS.My expertise spans designing Medallion Architectures (Bronze–Silver–Gold), implementing SCD Type 2 pipelines, optimizing ELT workflows, and integrating AI models for natural language–to–SQL conversion and automated analytics. I’ve built and deployed a GenAI-powered Cortex Analyst Agent that enhanced business self-service analytics and improved decision-making efficiency across the enterprise.At Brinks, I engineered data pipelines that processed over 13B+ transaction records, automated data quality validation, and reduced compute costs through advanced task orchestration and error handling. My work has consistently improved data reliability, reduced operational overhead, and enabled faster insights for analytics teams.With a Master’s in Computer Science from the University of Texas at Arlington and a Bachelor’s in Computer Science from BMS College of Technology and Management, I’m passionate about leveraging data, AI, and cloud technologies to build innovative, high-impact solutions that empower data-driven decisions.

Experience

1. Data Engineer

   Brink’s Inc

   Mar 2025 — Present · Dallas, TX, US

   Designed and developed large-scale ETL pipelines in Informatica IICS processing 13B+ records, enabling high-performance ingestion, transformation, and Snowflake ELT workloads.• Built a GenAI-powered Cortex Analyst Agent supporting natural language → SQL conversion and automated visual insights to enhance business self-service analytics.• Integrated Snowflake Cortex Intelligence with domain-specific prompt tuning to improve analytical accuracy and contextual understanding.• Created a Streamlit UI for the Cortex Agent, enabling real-time data exploration through an intuitive interface.• Implemented automated Data Quality Alerts using Python and Teams webhooks for real-time exception monitoring and validation.• Architected a Medallion Data Architecture (Bronze → Silver → Gold) to streamline ingestion, cleansing, enrichment, and consumption pipelines.• Re-engineered dimensional models to consolidate datasets, improving data consistency and simplifying downstream reporting.• Built SCD Type 2 pipelines for historical tracking and enterprise auditability.• Developed Snowflake-native components such as Dynamic Tables, Materialized Views, Stored Procedures, Streams, and Tasks to automate ELT frameworks.• Created incremental taskflows in IICS using watermark logic and advanced error handling to reduce compute costs and improve reliability.• Maintained SOX-compliant ETL pipelines, resolving data duplication and optimizing transformation logic.• Collaborated with the Power BI team to optimize Snowflake reporting views, improving dashboard performance and load times.• Integrated Snowflake REST APIs for secure JWT-based access and automated external connections.• Built custom GitHub Actions workflows to trigger Teams alerts for repository commits, enhancing CI/CD visibility and collaboration.

Education

• The University of Texas at Arlington

  Masters, Computer Science

  2022 — 2024

• Visvesvaraya Technological University

  Bachelor of Technology - BTech, Computer Science

  2017 — 2021