With over five years of experience as a Data Engineer , Priyank specializes in building scalable, data-centric solutions using Python. He has extensive, hands-on experience designing and implementing robust ETL pipelines for data extraction, transformation, and real-time analytics , leveraging technologies like Apache Spark, Pandas, NumPy, and AWS Glue. His proficiency extends to processing both structured and unstructured data, demonstrated by his project work building data pipelines to convert PDFs into structured JSON formats. Priyank is highly skilled in developing scalable microservices and RESTful APIs with backend frameworks such as Django, Flask, and FastAPI. He has deep knowledge of relational databases including PostgreSQL, MySQL, and Oracle , and has integrated real-time data streaming systems using Kafka. An expert in cloud-native deployment, he is proficient with both AWS (S3, ECS, Lambda, RDS) and Azure and is skilled in automating CI/CD pipelines with tools like Docker, Jenkins, and GitHub Actions. Complementing his backend and data engineering capabilities, Priyank develops intuitive user interfaces with React.js and is an excellent communicator with a strong background in Agile/Scrum collaboration.
AI, ML & LLM
Amazon Elastic Container Service (Amazon ECS)
AI/ML
LLMs
Developed ETL pipelines and REST APIs to process large-scale streaming data. Created a React.js front end for real-time Spark Streaming visualization with interactive dashboards. Migrated workloads to Azure for better scalability and performance. Implemented caching, query optimization, and logging for efficient operations. Built ETL pipelines using Django and Python. Developed REST APIs for real-time data access. Created front-end components in React.js for data visualization. Optimized data processing and implemented performance improvements. Managed cloud deployment, monitoring, and alerting using Azure Services.
Built a comprehensive data pipeline to extract structured information from PDFs and convert it to JSON format for further processing. Developed a React.js dashboard for monitoring pipeline status, error logs, and data processing metrics. Integrated FastAPI back end to provide real-time updates and API services. Implemented AWS-based storage and processing using S3, Lambda, and ECS. Ensured scalability, reliability, and automated error handling. Designed and implemented back-end services using FastAPI. Developed front-end dashboards using React.js. Managed data extraction pipelines and handled PDF to JSON transformations. Integrated AWS services for storage, compute, and deployment. Monitored system performance and optimized for reliability and scalability.
