Data Engineer Power Bi

Mohana Sree Kuppa

Data Engineer

Atlanta, GA 470-***-**** ******.*******@*****.***

SUMMARY

●4+ years of experience in data analysis and engineering, optimizing data pipelines to improve processing efficiency by 30%.

●Proficient in Python, R, SQL, and SAS, with a track record of developing predictive models that increased forecasting accuracy by 20%.

●Developed data visualizations with Tableau and Power BI, improving decision-making processes and boosting stakeholder engagement by 25%.

●Engineered and implemented ETL pipelines on AWS, reducing operational expenses by 20% and maintaining 99% data availability.

●Experienced in building data pipelines on cloud platforms such as Microsoft Azure, Snowflake, and Google Cloud Platform (GCP).

EDUCATION

Masters of Science in Computer Science Kennesaw State University - Atlanta, GA

Bachelors in Electronics and Communication Engineering Osmania University - Hyderabad, Telangana

SKILLS

Methodologies: Agile, Waterfall Language: Python, R, SQL, SAS IDEs: Visual Studio Code, PyCharm

Packages: NumPy, Pandas, Matplotlib, SciPy, ggplot2, Scikit learn, PySpark, Keras, TensorFlow, Apache Airflow

Visualization Tools: Tableau, Power BI, Microsoft Excel, Looker, Google Analytics

Database: MySQL, SQL Server, Mongo DB, Cassandra

Cloude technologies: AWS, S3, RDS,

Microsoft Azure (ADF, SSMS, Blob Storage)

Version Control Tools: Git

Operating System: Windows, Linux

Other Skills : DAX, Power Query, JIRA, Machine learning Algorithms

EXPERIENCE

Centene, GA March 2022- Present

Data Engineer

●Spearheaded the design and implementation of end-to-end ETL pipelines, increasing data handling capacity by 40% and improving overall data efficiency.

●Optimized data workflows using Python, SQL, and AWS tools (S3, RDS), leading to a 30% reduction in data processing times and faster data accessibility.

●Collaborated with cross-functional teams to define scalable data architecture, resulting in a 15% reduction in system downtime and enhanced infrastructure performance.

●Automated data validation processes, improving data quality by 20% and reducing manual error corrections significantly.

●Designed and implemented data models to support real-time analytics, driving enhanced decision-making capabilities across the company.

●Applied version control best practices using Git, improving collaboration efficiency across teams and enhancing code quality by 10%.

●Led the design and optimization of data pipelines using Python, R, and SQL, boosting operational efficiency by 15%.

●Engineered scalable data pipelines with PySpark, formatting data (JSON) for visualization, and creating dashboards, improving data processing speed by 25% and reducing latency in real-time data handling.

●Managed and simplified data storage solutions in Amazon S3, achieving 99% data availability and ensuring compliance with stringent security standards.

●Worked closely with teams to enhance data quality leading to a 20% increase in data-driven decision-making throughout the organization.

Apex Infolab, India

Data Engineer May 2019 - July 2021

●Collaborated closely with cross-functional teams in an Agile environment, improving communication efficiency and reducing data pipeline delivery timelines by 15%.

●Optimized data processing tasks by leveraging Python's data manipulation libraries (Pandas, NumPy), resulting in a 30% increase in productivity across data workflows.

●Developed dynamic and automated reporting pipelines using Power BI, leading to a 25% increase in strategic decision-making efficiency through real-time business intelligence insights.

●Conducted advanced statistical data analysis using R and SAS, contributing to predictive model development that improved sales forecast accuracy by 20%.

●Managed and restructured AWS infrastructure, reducing resource usage and cutting operational costs by 20%, while maintaining a 99% uptime for seamless data processing operations.

●Enhanced team collaboration through effective communication and critical thinking, resulting in a 10% decrease in project lead times and improved project outcomes.

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