Data Governance Engineer
Resume:
Pardhu Kancharla
Seattle, WA *******************@*****.*** 203-***-**** www.linkedin.com/in/pardhukancharla
Professional Summary
Results-driven Data Engineer with 2 years of full-time experience, specializing in data pipelines, cloud-based ETL solutions, and big data analytics. Proficient in SQL, Google Big Query, AWS Redshift, and Snowflake, with expertise in ETL tools, Apache Airflow, and data governance. Adept at building scalable data workflows, optimizing performance, and ensuring data integrity in cloud environments such as AWS, Google Cloud, and Azure.
Technical Skills
Programming Languages: Python, SQL, Shell Scripting
Databases & Big Data: SQL, Google Big Query, AWS Redshift, Snowflake
Data Pipelines & ETL: Google Dataflow, AWS Glue, Google Cloud Data Fusion
Workflow Orchestration: Apache Airflow, Prefect, Kubernetes
Cloud Platforms: AWS, Google Cloud Platform (GCP), Microsoft Azure
Data Visualization: Tableau, Power BI, Google Data Studio, Looker
Data Governance & Security: IAM, Compliance & Data Governance, GDPR, HIPAA
Databases & Big Data: SQL, Google Big Query, AWS Redshift, Snowflake
Data Pipelines & ETL: Google Dataflow, AWS Glue, Google Cloud Data Fusion
Workflow Orchestration: Apache Airflow, Prefect
Cloud Platforms: AWS, Google Cloud Platform (GCP), Microsoft Azure
Data Visualization: Tableau, Power BI, Google Data Studio
Data Governance & Security: IAM, Compliance & Data Governance
Professional Experience
Data Engineer
Client: Infotech Hyderabad, India Jan 2021 to July 2022
Developed and maintained ETL data pipelines using Google Dataflow, AWS Glue, and Google Cloud Data Fusion, ensuring efficient data movement and transformation.
Optimized Big Query, Redshift, and Snowflake queries, improving performance and reducing data processing time by 30%.
Designed and automated workflows with Apache Airflow and Prefect, reducing manual intervention in data pipelines by 40%.
Designed and implemented scalable data pipelines on Azure, leveraging Data Modeling, ETL (Extract, Transform, Load) processes, and Data Warehousing to efficiently process and store large datasets. Utilized Scala and C# to develop optimized backend services that integrate with M365 and RESTful APIs for seamless data flow.
Implemented data governance policies, ensuring compliance with cloud IAM and security best practices.
Developed interactive dashboards in Tableau, Power BI, and Google Data Studio, providing key insights to stakeholders.
Led AWS and GCP cloud migration initiatives, improving scalability and reducing operational costs.
Applied analytical skills and mathematical modeling to enhance predictive analytics in business intelligence solutions. Integrated Microsoft 365 services for seamless collaboration while ensuring secure authentication and authorization in cloud computing environments.
Integrated multiple data sources into cloud data warehouses using AWS Glue, Dataflow, and Big Query, streamlining data ingestion and transformation.
Built real-time data streaming solutions using Apache Kafka and AWS Kinesis, improving data availability and decision-making speed.
Data Engineering
Net soft Mate, India Aug 2020 to Jan 2021
Assisted in building and monitoring ETL pipelines for structured and semi-structured data.
Analysed large datasets using Big Query, AWS Redshift, and Snowflake to support data-driven decision-making.
Created automated workflows in Apache Airflow, improving the reliability of data ingestion processes.
Worked with data governance frameworks to enhance compliance and security in cloud environments.
Developed data visualizations in Power BI and Tableau for reporting and analysis.
Supported AWS and GCP cloud-based data warehouse optimization, enhancing query performance and storage efficiency.
Assisted in implementing CI/CD pipelines for automated deployment of ETL workflows, reducing deployment time by 50%.
Conducted cloud security assessments, ensuring compliance with industry standards for AWS and GCP environments.
Education
Master of Science in Computer/Information Technology Services and Management
Campbellsville University - Kentucky [ August 2024]
Bachelor of Science in Computer Science
Dhanakula Institute of Technology – Andhra Pradesh, India [ July 2020]
Projects
Automated Data Quality Monitoring System
Designed and implemented a data quality framework using Python and Apache Airflow.
Automated anomaly detection and alerting for data integrity issues across multiple pipelines.
Reduced data inconsistencies by 35% through proactive issue identification.
Real-Time Data Pipeline for E-Commerce Analytics
Built a real-time data pipeline using Apache Airflow and Google Dataflow to process streaming data from an e-commerce platform.
Stored processed data in Google Big Query and created interactive dashboards in Tableau for sales and customer behaviour analysis.
Cloud-Based Data Lake on AWS
Designed and implemented a data lake architecture on AWS using S3, Glue, and Redshift.
Automated data ingestion and transformation workflows using Python and AWS Lambda.
Data Governance Framework Implementation
Developed and implemented a data governance framework for a healthcare organization, ensuring compliance with HIPAA regulations.
Configured cloud IAM roles and policies to enforce role-based access control (RBAC).
Real-Time Data Pipeline for E-Commerce Analytics
Built a real-time data pipeline using Apache Airflow and Google Dataflow to process streaming data from an e-commerce platform.
Stored processed data in Google Big Query and created interactive dashboards in Tableau for sales and customer behaviour analysis.
Cloud-Based Data Lake on AWS
Designed and implemented a data lake architecture on AWS using S3, Glue, and Redshift.
Automated data ingestion and transformation workflows using Python and AWS Lambda.
Data Governance Framework Implementation
Developed and implemented a data governance framework for a healthcare organization, ensuring compliance with HIPAA regulations.
Configured cloud IAM roles and policies to enforce role-based access control (RBAC).
Achievements
Reduced data pipeline processing time by 25% through query optimization and parallel processing techniques.
Recognized as “Top Performer” during internship for contributions to data pipeline automation and documentation.
Developed a real-time monitoring system that improved data reliability by 40%.
Successfully led a team initiative to migrate legacy ETL workflows to a cloud-native architecture, enhancing scalability and cost-efficiency.
Delivered a data visualization solution that improved decision-making efficiency for business stakeholders by 20%.
Reduced data pipeline processing time by 25% through query optimization and parallel processing techniques.
Recognized as “Top Performer” during internship for contributions to data pipeline automation and documentation.
Delivered a data visualization solution that improved decision-making efficiency for business stakeholders by 20%.
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