Data Engineer Science

SAHANA MUDDULURU

Plano, TX 405-***-**** ***************@*****.*** LinkedIn

PROFESSIONAL SUMMARY

Knowledgeable AWS Data Engineer with 4+ years of experience managing and optimizing AWS cloud environments. Developed and implemented efficient data pipelines, enhancing data accessibility and reliability. Demonstrated expertise in automation and data storage solutions, coupled with strong problem-solving and analytical skills. Domain expertise in finance, healthcare, retail and telecommunications.

EDUCATION

The University of Texas at Dallas 01/2022 – 12/2023 Master of Information Systems and Management 3.6 GPA Relevant coursework: Big Data, Systems Analysis & Project management, Cloud Computing, Programming for Data Science, Database Foundations, Advanced Statistics for Data Science

SSN College of Engineering (Anna University) 05/2014 – 05/2018 Bachelors of Electronics and Communication 3.0 GPA TECHNICAL SKILLS

Programming & Scripting: Python (PySpark, Pandas, NumPy), SQL, SQLite Data Engineering & Visualization: Hadoop, Data Modeling, Power BI, MS Office, Tableau, Apache Spark, Apache Hive, Airflow Cloud Platform: S3, Lambda, EC2, EMR, Glue, Athena, CloudWatch, CloudFormation, RDS Tools & Technologies: JIRA, SharePoint, Tableau, GitHub Certification: Six Sigma (Green Belt), AWS Cloud Practitioner, Power BI Data Analyst Associate WORK EXPERIENCE

AWS Data Engineer Martingale Solution Group – Fixed term Contract 10/2024 – Current

• Automated and secured the transfer of sensitive files from an SFTP server to AWS S3 using AWS Lambda, improving data reliability and reducing manual errors by 90%, ensuring seamless daily operations

• Optimized ETL processes by leveraging Lambda along with Pandas and NumPy, reducing data cleaning and transformation time by 40%, which sped up analytics workflows and decision-making

• Implemented CI/CD pipelines using GitHub Actions to automate deployment of code updates to AWS Lambda, ensuring seamless and efficient continuous integration and delivery.

• Developing an application using Python, Django and SQLite to provide forecast of the financial risk growth. AWS Data Engineer Kode Systems 02/2024 – Current

• Designed scalable data pipelines to extract, transform, and load data from diverse sources into AWS S3, ensuring high reliability and reducing data processing time by 30% while consistently meeting critical business requirements.

• Managed and optimized data infrastructure, including S3 buckets, Databricks clusters, and Apache Airflow workflows, by monitoring performance, capacity, and cost, leading to a 25% reduction in operational expenses and enhanced system reliability.

• Leveraged Python and SQL in Windows environments to construct ETL pipelines, automation solutions, and data science tooling, enabling seamless data processing and reducing manual workloads by 40%.

• Executed intricate data matching and merging processes utilizing Kubernetes, PySpark, and fuzzy matching techniques, enhancing data quality and integrity.

AWS Data Engineer Home Depot (Client) 08/2023 – 12/2023

• Automated backup processes using AWS CLI for S3 buckets, enabling a 50% reduction in manual intervention and ensuring high reliability for critical data storage. Facilitated efficient file transfers to and from Amazon S3 and created nightly AMIs for production servers, improving disaster recovery readiness and system uptime.

• Designed logical and physical data models for diverse data sources in AWS Redshift, optimizing data storage and retrieval processes, resulting in a 30% improvement in query performance for business-critical analytics.

• Executed the migration of on-premises database structures to the AWS Redshift data warehouse, ensuring seamless data transition with zero downtime, which significantly improved system scalability and reduced maintenance overhead. Data Engineer TATA Communications – (Verizon and AT&T) 06/2018 - 11/2021

• Developed and deployed scalable data pipelines from requirements gathering to deployment, using Python, and SQL, and implementing Agile methodologies to ensure efficient delivery and testing cycles.

• Administered and enhanced MySQL databases, automating deployments and testing with Jenkins, which reduced deployment time by 30% and increased system reliability. Conducted MySQL training sessions that improved team efficiency and ensured consistent database performance and earned “Extra Mile Award”. ACADEMIC PROJECTS

• Conducted Twitter sentiment analysis using Python and SQL, scaling, normalizing, and imputing missing data to identify global sentiment factors.

• Executed a Big Data project on risky drivers using Python and SQL, visualizing results with Power BI, Tabulae, and VMWare.

• Designed and implemented Power BI dashboards by extracting data from Amazon Redshift and SAP, delivering actionable insights on revenue, gross profit, GP%, and financial metrics like Accounts Payables (AP) and Receivables (AR), which enhanced decision-making across customer, account manager, and regional performance.

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