SAI NITHIN MAIPATH

• Results-driven Data Engineer with 3+ years' experience in building and managing modern data stacks using modern deploying tools. I specialized in creating efficient data pipelines, cloud infrastructure automation, implementing data governance and Data Ops practices using GEN AI.
• Explored all the modern-day DevOps tools like harness and implemented CI/CD and chaos engineering along with intelligent rollbacks in a unified platform using harness delegates.
• Capable of extracting open-source codes and extending them to the company needs and Integrated AI with the resources and reduced the tool dependencies for data quality and other tasks
• I work with all the traditional data stacks and modern data stacks and can work on different tools for different data engineering and data analysis tasks
• In-depth knowledge of Apache Iceberg table formats and used its ACID capabilities and integration of it with Trino query engine for a complete data transformation of parquet, AVRO files to aggregated tables in medallion architecture.
• Worked with large unstructured data sets and helped in driving valuable insights using big data technologies and Integrated machine learning workflows into data pipelines, streamlining model deployment and management using Airflow. Optimized data preprocessing and feature engineering processes to enhance model performance and scalability, enabling seamless collaboration between data engineering and ML teams.

Data Engineer for Foodlytics – Analytical Solutions for Grocery Store Chain

Project Overview:
Developed end-to-end data pipelines for a grocery store chain to analyze operational data, focusing on trends like seasonality, daily sales, and category performance. Integrated real-time reporting with automated dashboards and implemented optimized workflows for cost-effective data management.

Business Value:

· We introduced weekend combo promotions based on sales trend analysis, resulting in a significant revenue boost and enhanced customer satisfaction.

· Delivered actionable insights into product and category trends, enabling better inventory management and reducing stockouts.

· Built centralized dashboards to empower stakeholders with real-time operational insights, driving data-driven decision-making across multiple stores.