Priyank J.

Priyank J.

Indore, India
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About Me

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

Frontend

React.js JavaScript Frontend Development React Hooks

Backend

Python Scripting FastAPI Python Flask REST APIs API Integration Django

Database

Oracle PostgreSQL MySQL

DevOps

Terraform AWS S3 Azure AWS ECR CI/CD Pipelines AWS Glue Docker AWS AWS Lambda AWS RDS Jenkins

QA & Testing

PyTest

Workflow

Confluence GitHub Actions Agile (Scrum) Postman GitLab CI JIRA

Other

Pandas Full Stack Development Redux ETL Pipelines Data Transformation Object-oriented Programming (OOP) Tensorflow spacy Scikit Learn RESTFul APIs Robot Framework Spark Numpy Kafka Distributed Systems

Work history

Upstack
Upstack
Data Engineer
2024 - Present (1 year)
Indore, India

  • Integrated Kafka pipelines for real-time data streaming and optimized back-end services.

  • Built and deployed recommendation engines and predictive analytics solutions with TensorFlow and Scikit-learn.

  • Deployed applications on AWS (S3, ECS, Lambda, EC2) with Docker-based CI/CD pipelines.

  • Collaborating with cross-functional Agile teams, ensuring timely delivery of business-critical solutions.

PythonFull Stack DevelopmentFastAPIDjangoWeb Applications Recommender Engine Predictive AnalyticsTensorflowScikit LearnKafkaCI/CD Pipelines AWSAWS S3Amazon Elastic Container Service (ECS) AWS EC2AWS Lambda DockerAgile
Strivepool
Strivepool
Software Engineer
2020 - 2024 (4 years)
India

  • Built ETL pipelines and RESTful APIs for data extraction, transformation, and analytics.

  • Developed scalable microservices architecture using FastAPI and Flask.

  • Implemented React.js dashboards for analytics and insights visualization.

  • Migrated services to Azure and optimized Spark Streaming workflows for real-time analytics.

  • Automated deployment/testing with PyTest, Jenkins, Docker, and GitHub Actions.

PythonETL Pipelines RESTFul APIs Microservices Architecture FastAPIFlaskReact.jsAnalytical Dashboards Data VisualizationSpark Streaming Azure GitHub Actions PyTestJenkinsDocker

Showcase

Artemis
Artemis

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.

Upstream
Upstream

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.

Education

Education
B.Tech Computer Science & Engineering
India