Ravi Sharma

Built data pipelines to move data from marketing platforms, Google Analytics, and other sources to Redshift using Matillion and Fivetran, ensuring seamless integration and efficient data processing.

Led the Migration from Dynamo to Redshift using Kinesis and S3 and Lambda.

Designed and managed data warehouses on Snowflake, optimizing data storage and performance for large-scale analytics and reporting tasks.

Automated many ETL processes to process billions of rows of data, which reduced the manual workload by 30 percent.

Ingested data from different sources using a combination of SQL, Python, Google Analytics, BigData, Redshift and S3 to create data views to be used in BI Tools like Tableau/Power BI.

Build CI/CD pipelines using Jenkins to make the deployment process smooth.

Utilized Snowflake to design and implement scalable data warehouses, optimizing data pipelines for efficient processing and real-time analytics.

Built a more efficient ETL using Airflow and Redshift.

Created monitoring alerts for data pipelines.

Created Data pipelines that ingested streaming and transactional data and output cleaned data to Redshift.

Data annotations on AI-Genrative Data.

Handling uploading data on AWS.

Process documentation, configuration, and production issues resolving.

• Worked on AWS Environment for application deployment.
• Created DMS pipeline to load the supplier data into S3
• Set up data pipeline using AWS DMS and Airflow
• Developed, implemented and maintained ETL pipeline on heterogeneous sources using Matillion resulting in a 20% reduction in data processing time.
• Designed advanced analytics ranging from descriptive to predictive models to machine learning techniques.
• Designed and implemented effective database solutions and models to store and retrieve data.
• Developed utility for uploading data from different sources to RDS using web scraping and python.
• Establish data integrity frameworks using AWS services over Redshift Data Lake ensuring a 95 % data accuracy rate.
• Optimize infrastructure and data pipelines along with swiftly resolving issues, resulting in a 10% increase in pipelines efficiency.

• Worked closely with the teams prioritize partner feature requests.
• Worked with clients post-implementation on user testing, debugging, support and maintenance
• Hardware data automation using socket programming python.
• Developed and maintain ETL pipeline for data automation on heterogenous sources
• Hardware data automation, filtering and cleaning using python .
• Analyzed Dataset's and designed ML model for future prediction.
• Maintain core modules for data Enrichment and Auditing Frameworks.
• Write automation python code to process the raw data (MySQL)using pandas to target staging system.
• Creating and Running Simple, Complex SQL Queries to analyze the data correctness.
• Performance tuning at mapping, session and database level and troubleshooting.
• Video Surveillance Analytics -Develop Machine Learning model for Image detection using CNN.
• Human - detection Analytics –Involved in Development to automate the process
• Drone turnaround time using Video feeds. Used Python, YOLO, OpenCV, Boto3,
• Develop python code/utilities to perform various OS and AWS Cloud Activities.