Naveen Krishna Devulapally

• Results-driven Data Engineer with over 4+ years of professional experience in designing, developing, and optimizing data pipelines and architectures.
• Skilled in ETL and data integration using Informatica, Talend, SSIS, Google Dataflow, AWS Glue and Azure Data Factory (ADF), as well as managing big data technologies within the Hadoop Ecosystem.
• Proficient in a wide range of programming languages including Python, Scala, R, and SQL, and experienced with essential data science packages such as NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, Seaborn, and TensorFlow. 
• Adept at leveraging cloud technologies from AWS, GCP, and Azure to deliver scalable and efficient data solutions.
• Expertise in database management with PostgreSQL, MS SQL, MySQL, Cassandra, and DynamoDB, coupled with advanced capabilities in data visualization using Tableau, QlikView, and Power BI. 
• Proficient in Unix Shell Scripting for automating tasks.
• Committed to continuous improvement and innovation in data engineering, utilizing a diverse array of technologies including version control (Git, GitHub), data cataloging (Alation), data analytics (ThoughtSpot), real-time data integration (Striim), job scheduling (Control-M, Airflow), SQL management tools (MySQL, PostgreSQL, SQL Server), cloud platforms (AWS, GCP, Azure), big data processing (Apache Spark, Hadoop), containerization (Docker, Kubernetes), and CI/CD pipelines (GitLab CI/CD) to ensure robust, maintainable, and high-performance data systems.

• Results-driven Data Engineer with over 4+ years of professional experience in designing, developing, and optimizing data pipelines and architectures.
• Skilled in ETL and data integration using Informatica, Talend, SSIS, Google Dataflow, AWS Glue and Azure Data Factory (ADF), as well as managing big data technologies within the Hadoop Ecosystem.
• Proficient in a wide range of programming languages including Python, Scala, R, and SQL, and experienced with essential data science packages such as NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, Seaborn, and TensorFlow. 
• Adept at leveraging cloud technologies from AWS, GCP, and Azure to deliver scalable and efficient data solutions.
• Expertise in database management with PostgreSQL, MS SQL, MySQL, Cassandra, and DynamoDB, coupled with advanced capabilities in data visualization using Tableau, QlikView, and Power BI. 
• Proficient in Unix Shell Scripting for automating tasks.
• Committed to continuous improvement and innovation in data engineering, utilizing a diverse array of technologies including version control (Git, GitHub), data cataloging (Alation), data analytics (ThoughtSpot), real-time data integration (Striim), job scheduling (Control-M, Airflow), SQL management tools (MySQL, PostgreSQL, SQL Server), cloud platforms (AWS, GCP, Azure), big data processing (Apache Spark, Hadoop), containerization (Docker, Kubernetes), and CI/CD pipelines (GitLab CI/CD) to ensure robust, maintainable, and high-performance data systems.

University of Illinois Springfield, IL 

Master's, Data Analytics