S

Sai Ganesh Polepalli

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Redmond, Washington, United States

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Résumé

Jobs verified_user 0% verified
  • Nordic Global
    Data Engineer and Analyst
    Nordic Global
    Jan 2024 - Current (2 years 9 months)
    2+ years of hands-on experience in designing and developing data warehouse (DWH) models using Data Build Tool (DBT) and SQL by applying medallion architecture principles to improve data traceability, accuracy, and downstream reporting performance.Built Power BI reports and dashboards for finance and business stakeholders, providing visibility into KPIs like Financial Forecast, Gross Profits, Revenue, Sales Win-Loss ratio which improved decision-making and operational efficiency.Collaborated with senior data engineers to optimize SQL queries and transformations and improve ETL pipeline performance, reducing data load times by 35% and enabling faster report delivery.Migrated data from Oracle NetSuite to Workday and Salesforce, ensuring data i
  • Atos
    Junior Data Engineer
    Atos
    Nov 2020 - Jul 2022 (1 year 9 months)
    Develop dashboards to help business users analyze data as well as providing data insight into upper management with a focus on Microsoft Power BI and composing queries to retrieve data from MSSQL server.Responsible for providing reports and some data metrics to both the operation team as well as vendors.Developed and maintained dynamic Power BI dashboards and reports by creating custom DAX queries and computed columns, leveraging data from MSSQL Server.Utilized Power BI Gateways to ensure real-time updates and delivered insightful visualizations as per business requirements.MSSQL Server and Familiarity with PowerBI.Troubleshoot and resolve technical issues related to the products within defined SLAs.
  • D
    ETL and Environment engineer
    Du Telecom
    Jun 2019 - Oct 2020 (1 year 5 months)
    Responsible for checking the flow of ETL pipelines in informatica and perform RCA on the raise of issue.Monitoring the server health and make sure Testing and production servers are running well and ETL pipelines are running on scheduled time.Performing code deployments and extracting data files that are required for production and testing data that are required for field engineers.Contributed to the development of automation tool called UCD for the code deployments with external teams and converted manual deployment to automation.Enhancing code and debugging the code deployments in the production servers and redeploying them for better performance.Worked an open-source server monitoring tool called Nagios to check server health and memory
Education verified_user 0% verified
  • Portland State University
    Master's in computer science
    Portland State University
    Jan 2022 - Jan 2024 (2 years 1 month)
    Majors: DBMS and SQL, Data Engineering, Data Analysis and Visualization, Cloud Systems.
  • Reva University
    Bachelor's in computer science
    Reva University
    Jan 2015 - Jan 2019 (4 years 1 month)
Projects (professional or personal) verified_user 0% verified
  • I
    IPL CSK Player Analysis
    Feb 2024 - Mar 2024 (2 months)
    Collected and enriched data from diverse sources such as Kaggle, Wikipedia, and IPLT20 using Python, pandas, and web scraping, ensuring accuracy and comprehensive coverage of all relevant fields.Conducted statistical analysis to derive actionable insights, providing valuable performance metrics and trend analysis of CSK players.Designed and developed interactive dashboards in Power BI, creating dynamic and user-friendly visualizations to showcase complex cricket data and statistics.Applied best practices in data visualization to effectively communicate findings, transforming raw data into compelling narratives about player performance.
  • T
    Tri-Met
    Nov 2023 - Mar 2024 (5 months)
    Extracted Tri-Met bus transportation data and stored it in Google Cloud Storage (GCS) using Dataproc clusters and Jupyter Notebook web interfaces, setting up a landing area for raw data.Performed data transformations within Dataproc, cleaning and enriching the dataset based on specific business requirements, then storing the transformed data in GCS as a curated zone for validation and further processing.Loaded data into Big Query from GCS as dimension tables, organizing the data into distinct categories (e.g., routes, schedules, and bus performance) for easier querying and efficient data retrieval.Created fact tables from the dimension tables, aggregating key metrics that facilitate in-depth analysis and support business insights on bus per