Sai K Email & Phone Number

Houston, Tx, Us

Charlotte, North Carolina, Us

• Architected and implemented a comprehensive AWS-based solution for monitoring and notifying schema changes across RDS and AWS Glue Catalog, enhancing data governance and schema consistency.• Developed and maintained SQL Server stored procedures, functions, triggers, and indexes, significantly improving database performance and reliability for critical energy operations.• Utilized SSIS to create and manage ETL processes, connecting to multiple data types and ensuring seamless data integration and processing.• Designed and implemented Concourse CI/CD pipelines for continuous integration and deployment of AWS Lambda functions, enhancing automation and reducing manual intervention in pipeline execution.• Developed Power BI and SSRS reports, providing advanced data visualization and reporting capabilities to support strategic decision-making.• Implemented and maintained a robust data ingestion pipeline from Kafka to AWS S3, utilizing AWS Lambda for efficient data processing and transfer, ensuring real-time data availability and integrity.• Configured AWS Glue Crawlers to update the Glue Catalog, automatically detecting and documenting schema changes from incoming data streams.

Basking Ridge, Nj, Us

• Leveraged Google Cloud Platform (GCP) and BigQuery to enhance data analytics capabilities, significantly improving data processing speed and accuracy for client projects.• Developed and optimized SQL queries and stored procedures in BigQuery, leading to a 20% increase in query performance and supporting large-scale data analysis.• Designed robust data pipelines using Google Cloud Dataflow, ensuring efficient data transformation and loading that supported real-time business intelligence.• Implemented data models and schemas in BigQuery, which facilitated complex data analysis and supported strategic decision-making for top management.• Automated data ingestion and ETL processes using Google Cloud Composer, enhancing operational efficiency and reliability in data handling.• Conducted detailed data quality assessments and validation, ensuring the integrity and accuracy of data in BigQuery for critical business operations.• Collaborated with cross-functional teams to integrate GCP solutions, enhancing overall system architecture and achieving seamless data flow across platforms.• Provided expert guidance on GCP best practices, optimizing resource utilization and cost management for cloud services.• Managed and optimized PowerShell or VBA scripts that interact with Power BI tenants or excel sheets, improving script efficiency and performance.• Mentored a team of junior developers in GCP and BigQuery, raising their productivity and technical skills by 30%.• Designed custom dashboards using Google Data Studio, improving data visualization and accessibility for business stakeholders by 40%.• Led the deployment of machine learning models on GCP, using BigQuery ML to predict market trends and inform business strategy.• Ensured compliance with data security and privacy standards in cloud deployments, maintaining high levels of data protection and trust. • Documented technical processes and trained end-users on new GCP features and BigQuery functionalities.

San Antonio, Texas, Us

● ● Containerized the application into a Docker file to run it universally and hosted it on Docker Hub.● Deployed the model on AWS SageMaker along with docker including security configurations for Docker image on CentOS.● Built the frontend of the application using MLFlow and Flask in order to compare the runs of the model and evaluate the KPIs for the model.● The vanilla version of code is deployed into AWS using Jenkins CI/CD pipeline and I’ve configured all of the requirements as per the architecture design. ● Improved algorithm accuracy from 86% to 94% efficiency using wildcard-based regex feature implementation for the existing NLP algorithms.Worked on building PySpark algorithms for different aggregations of data based on the specifications. ● Involved with performance and process enhancement of the PySpark framework.● Developed integration checks around the PySpark framework for Processing of large datasets. ● Worked on migration of PySpark framework into AWS Glue for enhanced processing. ● Wrote various automation scripts for automation of data processing on AWS Glue.● Developed data warehouse model in snowflake for over 100 datasets using where cape.● Build integration testing system that involved testing the entire framework with a code check in.● Used SAS - output delivery system ODS to format reports in HTML, PDF, CSV and RTF reports.● Created databases using MySQL, wrote several queries to extract data from the database.● Communicated effectively with the external vendors to resolve queries.Environment: Python, PySpark, Java, wxPython, Apache, AWSGlue, AWS Athena, AWS Step Functions, CloudFormation pytest, Bootstrap, Flask, Oracle, PL/SQL, MySQL, MS-SQL, REST, PyCharm, Windows, Linux.

Austin, Texas, Us

• Worked on predictive analytics use-cases using R language.• Use Python unit and functional testing modules such as unit test, unittest2, mock, and custom frameworks in-line with Agile Software Development methodologies.• Performed several roles in app development lifecycle serving enterprise clients in tech and fintech. Tech stack included Java, Python, HTML, CSS, SQL, NoSQL, and Oracle Cloud applications.• Interacted with clients' executives throughout entire project lifecycle from requirements gathering to maintenance. • Used Agile processes during implementation phase. Improved deliverables productivity by 20%. Completed deliverables 2 months faster.• Developed test scenarios and test cases, which achieved 95% success rate.• Built, enhanced, debugged, and troubleshot scalable enterprise software programs with 50,000+ lines of code.• Improved data mining processes, resulting in a 20% decrease in time needed to infer insights from customer data used to develop marketing strategies.• Used predictive analytics such as machine learning and data mining techniques to forecast company sales of new products with a 95% accuracy rate.• Increased data security by updating companywide encryption, steganography, IP security, and secure wireless transmission practices.• Automated Performance Improvement Plan process for 13 business units. Saved 600+ monthly work hours. • Developed ERP analytics dashboard delivering real-time overview of client CEO's 13 business units, and see quarterly predictions using analytics and machine learning. Boosted quarterly client business activity by 20%.• Integrated external modules into Oracle Cloud HCM. Developed custom reports with 2X speed.• Developed test scenarios and test cases, which achieved 95% success rate.• Performed an in-depth study about Elastic Search, Kibana, Logstash, Kafka, and Spark to establish