I am a results-driven Data Engineer with over one year of experience designing and building scalable ETL/ELT pipelines, multi-source data ingestion systems, and cloud-based data workflows. I am proficient in Python, PySpark, SQL, and Apache Airflow for large-scale data processing, transformation, and orchestration. My hands-on experience includes working with Google Cloud services such as BigQuery and GCS, as well as AWS S3 for data lake and warehouse workloads.
I have successfully built automated data pipelines with validation, quality checks, and error handling that have reduced manual processing effort by over 90%. My strong foundation in data warehouse concepts, batch processing, and supply chain analytics has been applied across manufacturing and logistics domains. I am passionate about leveraging data to drive business decisions and improve operational efficiency.
In my current role, I design and develop automated ETL/ELT pipelines using Python, Pandas, and PySpark to extract, transform, and load data from multiple formats into structured data warehouses. I have built multi-source data ingestion systems integrating various file formats and implemented automated data quality checks to improve accuracy and audit readiness.
I also design interactive Power BI dashboards for KPI monitoring and develop Microsoft Power Automate workflows and SharePoint/Teams integrations to automate internal business processes, significantly reducing manual effort in HR and operations. I collaborate closely with supply chain and operations teams to translate business requirements into automated data solutions and dashboard reports.
My projects include designing fully automated batch ETL/ELT pipelines orchestrated by Apache Airflow, building Python-based ETL automation systems for multi-source PO data extraction, and developing internal Microsoft Teams portals for business process automation. Additionally, I have experience in Excel data automation, category-based report generation, and full-stack web application development using Django and React.js.
I am committed to continuous learning and applying innovative data engineering solutions to solve complex business challenges. I thrive in collaborative environments and enjoy contributing to projects that enhance data accessibility and decision-making capabilities.
CGPA: 7.82
Percentage: 73.66%
Designed and developed automated ETL/ELT pipelines using Python, Pandas, and PySpark to extract, transform, and load data from multi-format sources into structured data warehouse outputs, reducing processing time from 2+ hours to under 4 seconds. Built multi-source data ingestion systems integrating Ariba, ClearOrbit, and PDF-based PO files with automated validation, quality checks, and error handling. Implemented automated data quality checks improving data accuracy and audit readiness. Designed interactive Power BI dashboards for supply chain KPI monitoring. Developed Microsoft Power Automate workflows and SharePoint/Teams integrations to automate internal business processes, reducing manual HR and operations effort. Built Microsoft Teams-based internal portal with automated forms and approval workflows. Performed large-scale data cleaning, transformation, and standardization. Collaborated with supply chain and operations teams to translate business requirements into automated data solutions and dashboard reports.
Collected and recorded machine production data for performance tracking and operational analysis. Performed data verification and validation using Microsoft Excel. Designed and maintained standardized Excel templates for operational reporting. Built Power BI dashboards to visualize machine performance metrics and production KPIs.
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