Nrupalini Goud Katagouni Email & Phone Number

Tallahassee, Florida, United States

I have extensive experience in designing and implementing scalable data pipelines using Azure Data Factory and developing optimized data models in Azure Synapse Analytics to support complex queries and analytics. My work includes managing data storage solutions such as Azure Data Lake Storage and Azure Blob Storage, as well as designing ETL processes and creating high-level design documents for data flow, extraction, and staging. I have a solid background in developing and optimizing Informatica mappings, orchestrating data pipelines, and using tools like SQL Server for creating complex SQL queries, views, and managing data in dimensional and relational data warehouses.In my role, I have developed Spark applications in both PySpark and Scala to handle data cleansing, transformation, and ingestion for machine learning and reporting purposes. I have implemented workflows in Hadoop using MapReduce, optimized HDFS storage, and scheduled automated data processing jobs using Control-M. My experience also extends to implementing and maintaining machine learning models in production environments with TensorFlow and PyTorch, and developing interactive Tableau dashboards and reports to provide actionable business insights.Additionally, I have managed continuous integration workflows using GitHub Actions and integrated Azure DevOps with Azure Repos for version control and automated code reviews. I have also maintained repositories on GitLab, managed user permissions, and created Jira tickets for effective team communication on data pipeline issues and enhancements. My proactive involvement in status meetings and updates has ensured seamless project management and alignment with team goals.

San Francisco, California, United States

I have designed and implemented scalable ETL pipelines using AWS Glue to efficiently transform and load data while automating workflows and orchestration with AWS Step Functions and Lambda. My experience includes monitoring AWS resources with CloudWatch, developing Glue Crawlers, and creating data catalog tables. I have also developed Python scripts to transfer data and extract information from on-premises systems to AWS S3. I utilized PySpark for data ingestion and complex transformations, optimized SQL queries in SparkSQL for large-scale analytics, and leveraged Kafka REST APIs and Spark streaming for real-time data processing and integration with Hadoop and NoSQL stores.I have hands-on experience in managing and optimizing databases, including SQL Server, MySQL, and Amazon Redshift. I have utilized tools such as Informatica ETL for data workflows, transformations, and Snowflake for schema design and query optimization. My expertise extends to using Spark and Scala to develop machine learning algorithms, managing Control-M job issues, and ensuring efficient data retrieval and visualization in Power BI. Additionally, I have managed version control and code collaboration using GitHub, employed GitLab CI/CD pipelines for automation, and utilized Jira to streamline data engineering processes.Throughout my career, I have actively participated in weekly walkthroughs and inspection meetings to verify testing efforts and overall project status. I am committed to maintaining data security and compliance while creating and managing Power BI work spaces and datasets. My technical proficiency is complemented by strong problem-solving skills and the ability to implement process improvements, ensuring optimal performance in data engineering projects.

New Delhi, Delhi, India

I have developed and managed data pipelines using Azure Data Factory to orchestrate ETL workflows and ensure data quality, while also designing and implementing scalable data solutions on Azure Synapse Analytics for real-time analytics and reporting. I have optimized data storage and retrieval processes by leveraging Azure Blob Storage and Azure Data Lake Storage and have experience in dimensional modeling, data migration, data cleansing, data profiling, and ETL processes for data warehouses. Additionally, I have created and managed Informatica repositories, configured connections for data integration, and built ETL workflows across multiple sources using Azure Data Factory. My expertise extends to developing monitoring and notification tools in Python and writing Spark applications in Scala and Python (PySpark) to extract and analyze data from large datasets.I have designed and implemented various scalable systems using Hadoop technologies, including HDFS, MapReduce, Hive, and PIG, and have hands-on experience in data analysis within the Hadoop ecosystem. Furthermore, I have developed complex ETL workflows using Apache Airflow, optimized complex T-SQL queries and stored procedures for high performance, and managed data migration tasks and ETL processes using MySQL Workbench and other data integration tools. My background also includes creating and managing Power BI workspaces, datasets, and dataflows for efficient reporting, as well as automating deployment processes with Git hooks and CI/CD pipelines.In my projects, I have utilized GitHub Actions to automate testing, building, and deployment processes and managed agile project management tasks through Jira, including creating and managing user stories, tasks, and bugs. I have actively participated in code reviews, meetings, and technical discussions, contributing to solving complex technical issues and enhancing the overall project development process.

Mumbai, Maharashtra, India

During my career, I have optimized data access and retrieval performance through AWS DynamoDB for NoSQL databases and designed data pipelines using AWS Glue for efficient ETL processes. My experience includes utilizing AWS Redshift for data warehousing, focusing on schema design and performance tuning, and managing data lakes on AWS S3 to ensure effective data storage and retrieval. I have also developed and optimized data processing pipelines using components from the Hadoop ecosystem, such as HDFS, Hive, MapReduce, and Apache Spark, and implemented data ingestion and transformation workflows with tools like Apache Kafka, NiFi, Flume, and Sqoop.In addition, I have administered and optimized various relational databases, including MySQL, PostgreSQL, SQL Server, and Oracle, and created dynamic, real-time dashboards using Excel pivot tables and charts. I have experience building interactive dashboards and reports in Power BI, utilizing SAS and Google Analytics for comprehensive data analysis and reporting to support business strategy and operations. My work has involved applying machine learning models and statistical techniques using Scikit-learn, TensorFlow, and PySpark to extract valuable insights and predict trends.Furthermore, I have implemented infrastructure as code and automated workflows using Ansible and Terraform, enhancing operational efficiency and reducing manual intervention. I have developed and documented analytical processes and results using Jupyter Notebook and R Markdown, ensuring reproducible research and effective collaboration among teams. My experience spans various tools and platforms, contributing to a solid foundation in data engineering, analytics, and machine learning.