Tinku Kumar · Senior Azure Data Engineer · 7+ yrs
SeniorAbout Tinku
Tinku Kumar is a Data Engineer with 7+ years of experience in core data engineering roles, specializing in ETL processes and real-time analytics. He has a proven track record in Azure Cloud deployments and workflow orchestration using Apache Airflow.
7+ years of commercial experience in
Skills(20)
Why hire Tinku?
Designed and developed scalable ETL processes and data integration solutions.
Implemented machine learning algorithms for predictive maintenance in IoT contexts.
Managed data integration from multiple sources using Airbyte.
Successfully designed and developed ETL processes and data pipelines for real-time analytics using Apache Airflow and Apache Pinot.
Project highlights(5)
ETL Process and Data Pipeline Development for Real-time Analytics – Senior Software Engineer
Overview: This project focused on building robust ETL processes and data pipelines to support real-time analytics. Responsibilities: Designed and developed ETL processes to extract, transform, and load data from various sources into a centralized data warehouse. Implemented data pipelines using Apache Airflow to automate data workflows and ensure timely data delivery. Utilized Apache Pinot for real-time data analytics, providing insights into data trends and patterns. Deployed solutions using Azure Blob Storage, Azure SQL DB, and AKS. Ensured data quality, integrity, and security throughout the ETL processes.
Key outcomes:
Successfully designed and developed ETL processes for real-time analytics.
Ensured timely data delivery through automated Apache Airflow pipelines.
Predictive Maintenance – Senior Software Engineer
Overview: This project focused on developing a predictive maintenance solution using real-time IoT data and machine learning. Responsibilities: Developed ETL pipelines to gather real-time data from IoT devices and sensors. Implemented machine learning algorithms to perform predictive maintenance and anomaly detection. Utilized Azure IoT Analytics and Azure Machine Learning for data processing and model training. Created visualizations and dashboards to monitor the health and performance of industrial equipment. Integrated IoT protocols such as OPCUA and MQTT for data collection.
Key outcomes:
Implemented machine learning algorithms for predictive maintenance and anomaly detection.
Created visualizations for monitoring industrial equipment health and performance.
Web Scraping and Data Aggregation for Market Analysis – Senior Software Engineer
Overview: This project developed custom web crawlers to scrape data from competitor websites for market analysis. Responsibilities: Developed custom web crawlers to scrape data from competitor websites and aggregate the data for market analysis. Implemented ETL pipelines to clean, transform, and load the scraped data into a data warehouse. Utilized Azure services for scalable data storage and processing. Developed data analytics using Apache Pinot.
Key outcomes:
Developed custom web crawlers for competitor market analysis.
Implemented ETL pipelines for cleaning and transforming scraped data.
Document Parsing and Data Extraction using OCR – Senior Software Engineer
- This project involved extracting and transforming data from scanned documents and PDFs using OCR technologies.
- It focused on developing algorithms for data extraction and parsing integrated with RESTful APIs.
- Developed ETL processes to extract and transform data from scanned documents and PDFs using OCR technologies.
- Created algorithms for data extraction and parsing, integrating with RESTful APIs for data retrieval and storage.
- Ensured data accuracy and consistency through validation and error handling mechanisms.
- Deployed solutions using Azure Blob Storage for scalable storage.
Key outcomes:
Developed ETL processes for extracting and transforming data from scanned documents.
Ensured data accuracy and consistency through validation and error handling.
Web Scraping and Data Aggregation for Market Analysis – Senior Software Engineer
- This project developed custom web crawlers to scrape data from competitor websites for market analysis.
- It implemented ETL pipelines to process scraped data and utilized Apache Pinot for data analytics.
- Developed custom web crawlers to scrape data from competitor websites and aggregate the data for market analysis.
- Implemented ETL pipelines to clean, transform, and load the scraped data into a data warehouse.
- Utilized Azure services for scalable data storage and processing.
- Developed data analytics using Apache Pinot.
Key outcomes:
Developed custom web crawlers for competitor market analysis.
Implemented ETL pipelines for cleaning and transforming scraped data.
Industry experience
Logistics & Supply Chain
3 projects- •ETL Process and Data Pipeline Development for Real-time Analytics— Senior Software EngineerPython · Apache Airflow · Apache Pinot · Azure Blob Storage +2
- •Web Scraping and Data Aggregation for Market Analysis— Senior Software EngineerPython · Beautiful Soup · Pandas · Azure Blob Storage +2
- •Web Scraping and Data Aggregation for Market Analysis— Senior Software EngineerPython · Beautiful Soup · Pandas · Azure Blob Storage +3
Manufacturing & Industrial
1 project- •Predictive Maintenance— Senior Software EngineerPython · Azure IoT Analytics · Azure Machine Learning · Apache Airflow +2
SaaS / B2B
1 project- •ETL Process and Data Pipeline Development for Real-time Analytics— Senior Software EngineerPython · Apache Airflow · Apache Pinot · Azure Blob Storage +2
At a Glance
Single contract. No agency markup confusion.
Typically responds within 4 business hours.
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Tinku Kumar
Azure Data Engineer