Hitesh · Azure / GCP Data Engineer · 2.5+ yrs
JuniorAbout Hitesh
Hitesh is a Data Engineer with 2. 9 years of experience specializing in cloud data solutions and ETL development.
2.5+ years of commercial experience in
Skills(29)
Why hire Hitesh?
Designed and implemented end-to-end data solutions for Business Intelligence and Data Warehousing.
Managed deployments through CI/CD pipelines using Jenkins and Git.
Performed data migration to GCP Cloud Storage using Airbyte.
Successfully migrated data to GCP Cloud Storage, enhancing data accessibility.
Delivered high-quality solutions that exceeded expectations and provided measurable value to clients.
Played a crucial role in performing complex data transformations using Azure Databricks.
Project highlights(5)
Supply Chain Capacity Management – Data Engineer
Overview: Developed a capacity inventory management system for production centers and warehouses. Responsibilities: Utilized Azure Data Factory for simple transformations and data flows, creating pipelines to store EDL data in ADLS. Transformed Excel file data using Databricks and loaded it into SQL tables. Implemented Agile methodologies with 15-day scrum sprints, managing deployments through CI/CD tools like Jenkins and Git.
Key outcomes:
Created relational finished tables for the Polaris application.
Ensured fast performance for specific product visualizations.
Social Media Content Moderation – Content Moderator
Overview: Involved in validating social media content. Responsibilities: Ensured compliance and quality of social media content.
Key outcomes:
Validated social media content.
Project 3 – Data Engineer
- Designed and implemented end-to-end data solutions including Business Intelligence, Data Warehousing, Data Analysis, Schema Design, Data Visualization, and ETL Development using Azure Data Factory and Azure Databricks.
- Leveraged a robust technology stack that included Python, Pyspark, Pandas, and SQL.
- Managed CI/CD processes with Jenkins and Git for continuous delivery.
- Collaborated with cross-functional teams to deliver timely, accurate, and relevant data insights to business users.
- Committed to delivering high-quality solutions that exceeded expectations and provided measurable value to clients.
Key outcomes:
Designed and implemented end-to-end data solutions.
Delivered high-quality solutions that exceeded expectations and provided measurable value.
Collaborated effectively to deliver timely, accurate, and relevant data insights.
Polaris, Capacity Inventory Management – Data Engineer
- Developed a capacity inventory management system for production centers and warehouses, forecasting demand and visualizing it on Tableau dashboards.
- Focused on creating relational finished tables by extracting raw data from various sources such as Excel files, enterprise-level Data Layer (EDL), and Data Lake.
- Utilized Azure Data Factory for simple transformations and data flows, creating pipelines to store EDL data in ADLS.
- Transformed Excel file data using Databricks and loaded it into SQL tables.
- Implemented Agile methodologies with 15-day scrum sprints, managing deployments through CI/CD tools like Jenkins and Git.
- Employed Sonar Cube for static analysis and accessed artifacts via JFrog Artifactory to enhance testing and performance.
Key outcomes:
Created relational finished tables for the Polaris application.
Ensured fast performance for specific product visualizations by adding cleansing and manipulation code.
Managed deployments through a CI/CD pipeline connected to Git repository.
Project 5 – Data Engineering Intern
- Gained practical experience in industry-standard data tools.
- Designed and implemented ETL pipelines for large datasets.
- Utilized tools such as Hadoop, Shell Scripting, SQL, Python, ASP.NET, and Microsoft Excel.
- Focused on ETL pipeline development using Python and SQL.
Key outcomes:
Gained practical experience with industry-standard data tools.
Designed and implemented ETL pipelines for large datasets.
Industry experience
Logistics & Supply Chain
3 projects- •Supply Chain Capacity Management— Data EngineerAzure Data Factory · Databricks · SQL · Jenkins +1
- •Project— Data EngineerAzure Data Factory · Databricks · Python · Pyspark +11
- •Polaris, Capacity Inventory Management— Data EngineerTableau · Azure Data Factory · ADLS · Databricks +10
Manufacturing & Industrial
3 projects- •Supply Chain Capacity Management— Data EngineerAzure Data Factory · Databricks · SQL · Jenkins +1
- •Project— Data EngineerAzure Data Factory · Databricks · Python · Pyspark +11
- •Polaris, Capacity Inventory Management— Data EngineerTableau · Azure Data Factory · ADLS · Databricks +10
At a Glance
Single contract. No agency markup confusion.
Typically responds within 4 business hours.
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Hitesh
Data Engineer GCP