Ram Sirusanagandla

Experience

• 

  Zensar Technologies

  Jan 2020 - Apr 2021

  Data Engineer

  * As Zensar Client, Created interactive dashboards in Azure Synapse Analytics to visualize key performance indicators (KPIs), leading to a 10% improvement in data-driven decision-making.* Used Azure Databricks to perform complex data transformations on large datasets, achieving a 40% reduction in processing time compared to traditional methods.* Leveraged PySpark for large-scale data processing and analytics tasks within the Apache Spark ecosystem and utilized DataFrames and SQL functionalities for efficient data manipulation.* Created HiveQL queries that identified a 30% increase in customer churn rate, allowing for targeted customer retention campaigns.* Utilized Azure Functions triggers (Blob storage triggers) to automate data processing workflows upon arrival of new data in Azure Blob storage.* Created a Power BI dashboard to visualize key business KPIs, resulting in a weekly time savings of 2 hours on reporting tasks. Show less

• 

  Cognizant

  Apr 2021 - Dec 2022

  Engineered robust cloud solutions leveraging a comprehensive suite of AWS services, including Lambda, SNS, EC2, RDS, IAM, and more, to architect and implement scalable and reliable systems.Strategically devised robust data storage solutions utilizing S3 and seamless migration via Lambda functions.Crafted precise SCD2 SQL and Python scripts to fortify data integrity, scalability, and accessibility, orchestrating meticulous data structuring and cleansing in a data warehouse, achieving over 99% accuracy with procedures.Implemented CI/CD pipelines using tools like Jenkins, GitLab CI/CD, and AWS CodePipeline to automate the build, test, and deployment of data engineering applications.Accelerated data retrieval by optimizing SQL queries, resulting in significant performance gains. Improved data accessibility and scalability through the creation of comprehensive ERDs using Lucidchart.Implemented Lambdas using Python using NumPy, and pandas which parsed .xlxs files and processed them into parquet.Engineered and implemented a pioneering script to optimize the operational efficiency of Lambda, resulting in a 39% reduction in execution time and executable code into production with a flawless success rate of 100%. Show less Architected and implemented Azure Data Factory pipelines, optimizing ETL processes by 29% through strategic migration to a custom tool and leveraging Azure Data Lake for SFTP, CSV, and XML data storage.Used ADF components including linked services, copy services, functions, and HDInsight to streamline data handling and ensure compliance with industry standards.Spearheaded PySpark and Data Warehouse project, delivering a 43% performance boost through innovative optimization techniques.Leveraged Hive, Kafka, Spark, Snowflake, and Scala to process and analyze over 30GB of daily data stored in Parquet, ORC, and Avro formats.Utilized Cloudera for managing, processing, and analyzing large datasets. Skillfully integrated Databricks notebooks into pipelines, optimizing execution speed by 45%, and rigorously cleaned over 90% of the dataset to maintain data integrity. Show less

  • AWS Data Engineer

    Sept 2021 - Dec 2022

  • Azure Big Data and ETL Developer

    Apr 2021 - Sept 2021
• 

  TGS Technology LLC

  Jan 2024 - Jun 2024

  Data Engineer/ AI Engineer

  Developed ETL processes, data ingestion pipelines, and transformations for data integration and analytics in AWS. Migrated and analyzed over 200GB of data using Tableau, Databricks, EMR, Python, and Spark to uncover actionable insights.Integrated Apache Kafka with Airflow for real-time data ingestion from streaming sources, enabling near-real time data analysis and decision-making.Improved data pipelines using AWS Glue and Spark to improve data processing efficiency, resulting in a 20% reduction in data processing costs.Created an ML model using SVR Random Forest, implemented in SageMaker, and achieved 92% accuracy.Converted natural language questions into optimized queries using Codex, utilized LSTM, Docker, Bedrock, and ThoughtSpot for visualization, and conducted POCs on GenAI tools like Gemini, Bedrock, OpenAI, and Llama. Show less

• 

  Cerebrone.ai

  Jul 2024 - now

  Data Engineer/ AI Engineer

  * Architecting and maintaining robust data infrastructure to support real-time analytics and reporting, leveraging technologies such as Kafka, MongoDB, and AWS to ensure seamless data flow and integrity.* Developing and deploying scalable data pipelines using Kafka and RESTful APIs to process and analyze real-time streaming data, improving data processing speed by 40%* Implementing IaC with Terraform to automate the provisioning of AWS resources, reducing deployment time by 50% and GitLab for deployment, ensuring consistent environments across development, testing, and production.* Designing and orchestrating containerized applications using Kubernetes to manage microservices architecture for GenAI-based analytics solutions, enhancing system reliability and reducing downtime by 30%. Show less