I'm a Senior Data Engineer with a passion for AI, Data Science, and Full-Stack Development. With a Master's in Machine Learning & Data Science, I specialize in designing and implementing scalable, distributed systems that harness the power of big data and AI to drive transformative business outcomes.

• Data Engineering & ETL Pipelines: Architecting robust, scalable data pipelines using Apache Airflow, dbt, and Spark, ensuring efficient data ingestion, transformation, and delivery across cloud platforms.
• AI & Machine Learning Solutions: Building production-ready ML models leveraging TensorFlow, PyTorch, and Hugging Face Transformers for predictive analytics, NLP, and computer vision applications.
• Full-Stack Development: Creating seamless end-to-end applications with Django, FastAPI on the backend, and React.js on the frontend, integrating RESTful APIs and GraphQL.
• Cloud Infrastructure & DevOps: Designing cloud-native architectures on AWS, Azure, and GCP using Terraform, Docker, and Kubernetes to ensure high availability, scalability, and security.

• LinkedIn
• Portfolio
• Kaggle
• Medium

1. AI-Powered Predictive Analytics Platform: Engineered an end-to-end ML pipeline for demand forecasting, reducing forecasting errors by 20%. Integrated Kafka for real-time data streaming and ElasticSearch for fast data retrieval.
2. Cloud-Native ETL Pipelines: Developed automated, scalable ETL workflows using Apache Airflow, AWS Glue, and S3, processing terabytes of data with fault-tolerant, distributed systems.
3. Full-Stack Data Visualization Dashboard: Built a dynamic, real-time dashboard using Django REST Framework and React.js with WebSocket integration for live data updates.
4. MLOps Pipeline Implementation: Automated the lifecycle of machine learning models using MLflow, Kubeflow, and GitHub Actions, ensuring reproducibility and continuous deployment.

• Contributing to open-source projects in AI, Data Engineering, and Full-Stack development, focusing on optimizing large-scale data pipelines and AI models.
• Exploring serverless architectures with AWS Lambda and Google Cloud Functions for efficient resource management and scalability.
• Building a microservices-based architecture for modular, maintainable applications using Docker Swarm and Kubernetes.
• Implementing data governance and data lineage solutions to ensure data quality, compliance, and traceability.

• Languages: Python, SQL, JavaScript, Bash, YAML
• Frameworks: Django, FastAPI, React.js, Node.js, Flask
• Data Engineering: Apache Airflow, dbt, Spark, Kafka, Delta Lake, Snowflake
• AI/ML Libraries: TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, OpenCV
• Cloud Platforms: AWS (EC2, S3, Lambda, Glue), Azure (Data Factory, Functions), GCP (BigQuery, Cloud Functions)
• DevOps & Infrastructure: Docker, Kubernetes, Terraform, GitHub Actions, MLflow, Kubeflow
• Databases: PostgreSQL, MongoDB, MySQL, Redis
• Monitoring & Logging: Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana)

When I’m not crunching data or coding, you’ll find me designing custom SVG graphics for my projects, experimenting with cloud infrastructure automation, or diving into the latest open-source contributions. I'm always excited to tackle new challenges and explore emerging technologies!