Data Engineer with 4+ years of experience in designing, building, and optimizing scalable data pipelines and cloud-based data solutions. Strong expertise in Python, SQL, AWS, ETL/ELT pipelines, and Power BI. Experienced in automation, analytics-driven product delivery, and end-to-end data architecture design with a focus on performance, reliability, and business impact.
Overview
5
5
years of professional experience
1
1
Certification
Work History
Senior Data Engineer
Meditab software Pvt. Ltd.
Ahmedabad, Gujarat
02.2021 - 07.2025
Created interactive visualizations and reports using Power BI and Google Data Studio.
Automated tasks with Python scripts, improving team productivity and reducing errors.
Fine-tuned query performance and optimized database structures.
Reduced ETL runtime by 45% using DBT models and Prefect orchestration.
Designed and optimized ETL/ELT pipelines across multiple data sources.
Automated reconciliation and validation processes to improve data accuracy.
Tuned SQL queries and database schemas for scalability and performance.
Project's in multiple services: Data Extraction, Data conversion, Data Merging, Data Splitting, and Custom Reporting.
Data Engineer
Catalyst Partners Pvt Ltd
Ahmedabad, Gujarat
01.2021 - Current
Working in a multi-functional role covering data engineering, automation, BI reporting, and product-based client solutions.
Designed and implemented cloud-native data solutions on AWS, including scalable data workflows and automation frameworks.
Built and maintained end-to-end data pipelines ensuring performance, security, and cost efficiency.
Developed Power BI dashboards and analytical reports for business and client stakeholders.
Used Git for version control and collaborative development for the Products.
Data Archival Project, Django web application project. The data archival project involved leveraging the Django framework and PostgreSQL database to create a secure and user-friendly web application for clients to access their archived data. The system incorporated data retention policies, encryption and access control measures to meet compliance requirements. The project ultimately provided clients with a convenient and reliable solution to retrieve and view the archived data through a well designed web interface.
Data Merging Project, Data Merging Project using Python to automate the consolidation of data from multiple clients who decided to collaborate and work together. The primary purpose of the project was to streamline the data Merging process, reduce manual effort and improve efficiency. Utilized various data preprocessing techniques, including data cleaning, standardization and transformation to ensure consistency across the merged dataset.
Automated Custom Interface, Developed a Python-based utility to fully automate the end-to-end data transfer process. The solution handles data extraction from the database, transformation, and secure transfer to the client's server. It also includes robust logging, failure tracking, and automated email reporting to both the project owner and client, ensuring complete transparency and operational efficiency.