Skip to main content
Pavan Kumar M

Pavan Kumar M

Data Engineer

Talent
Bengaluru, Bengaluru Urban1000 INR/hourMember since October 24, 2024
·

Hire their services

Request a quote with no obligation

About

Working as Data Engineer at Startup for IoT Product client and previously for Britannia FMCG.

I have skills in Python, Mysql, MongoDb, Redis, Airflow, AWS (S3, Cloudwatch, lambda and Redshift), Docker and Kafka. Currently working on my Pyspark things.

Experience

Britannia BrandOps Sales Analysis Data Pipeline

•

Engineered a comprehensive ETL pipeline for a leading FMCG brand, streamlining the extraction and transformation of sales data, enhancing reporting accuracy and speeding up decision-making processes by 40 hours monthly.

•

Optimized SQL queries and data processing workflows, reducing execution time by 30% and improving system efficiency.

•

Integrated AWS services (S3, Lambda, Redshift) with data processing pipelines, enabling real-time analytics and streamlining reporting processes.

•

Developed interactive dashboards using Tableau, enhancing data visualization and accessibility for stakeholders,

thereby supporting business intelligence efforts.

•

Worked with cross-functional teams to implement data warehousing solutions, enhancing data accessibility and supporting business intelligence initiatives.

•

Managed Dockerized applications for efficient deployment and container orchestration, ensuring seamless integration with Apache Airflow for task automation.

Smart Grow Agritech IoT Product Data Pipeline

•

Led the Smart Grow project aimed at optimizing plant growth data management and quality control operations,

improving data processing speed by 50%.

•

Engineered robust data pipelines to process over 10,000 sensor data points and integrate them with lab results for real-time tracking and analysis using Kafka, MongoDB, and Airflow.

•

Developed a system that automatically creates and updates mileposts, providing insights into 95% of plant growth stages and quality metrics.

•

Structured data to ensure seamless integration with QBench, improving workflow efficiency by 30%.

•

Leveraged Docker and Airflow for automating task orchestration and containerized deployments, facilitating efficient handling of large data volumes.

•

Processed over 1 million records, significantly improving decision-making for agronomic operations

Education

bachelor's of Education (Electronic and Communications Engineering)

Reviews

Related