Sr Software Developer & Big Data Architect (python, java, Spark, Kafka, Hadoop, hive, Django & flask, Azure and AWS)

I am a seasoned professional experienced in designing, developing, and maintaining robust data engineering solutions and full-stack applications. With a strong background in data engineering, I excel in building scalable and distributed systems for processing and analyzing large datasets in real-time.

In terms of programming languages, I possess advanced proficiency in Python, Java, and SQL, leveraging their power to implement efficient and optimized solutions. I have extensive experience working with Apache Spark, utilizing its capabilities for big data processing and analytics.

My expertise extends to various cloud platforms, including AWS, Azure, and GCP. I am well-versed in deploying and managing applications in cloud environments, utilizing services such as AWS Lambda, S3, EMR, Azure Data Lake, and GCP BigQuery.

As a full stack developer, I have hands-on experience with web frameworks like Flask, Django, and Spring Boot, enabling me to build scalable and responsive web applications. I am adept at containerization technologies such as Docker and orchestration tools like Kubernetes for deploying and managing microservices architecture.

Furthermore, I possess knowledge of message streaming systems, particularly Apache Kafka, for building real-time data pipelines and event-driven architectures. I have experience with configuration management tools like Ansible to automate and manage infrastructure as code.

With proficiency in front-end development, I can create dynamic and interactive user interfaces using Angular, ensuring a seamless user experience.

As a senior data engineer and full stack developer, I am highly skilled in problem-solving, system architecture design, and performance optimization. I am dedicated to delivering high-quality solutions and staying up to date with the latest technologies and industry best practices.

Overall, I bring a wealth of experience and a comprehensive skill set to contribute to the success of data-driven projects and full-stack development endeavors.