Rohit Bomte

Data Engineer

Nagpur, Maharashtra, India0 mo experience

Key Highlights

Hands-on experience in building ETL pipelines.
Proficient in data analysis and visualization tools.
Strong problem-solving and critical thinking skills.

Stackforce AI infers this person is a Data Engineer with a focus on ETL processes and data analytics.

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Skills

Core Skills

Data EngineeringData AnalysisData Analytics

Other Skills

Apache AirflowETL PipelinesPython (Programming Language)PythonSQLPower BIData ValidationData Quality ChecksSource Data MonitoringData ExtractionMonitoring & AlertingWorkflow OrchestrationRedashScriptingWeb Scrapping

About

Hello! I’m currently working as a Data Engineer Intern, gaining hands-on experience in building and maintaining end-to-end ETL pipelines using Apache Airflow, Python, and SQL.My work involves web scraping data from client native websites and multiple e-commerce platforms, followed by data cleaning, transformation, and loading based on business requirements. I’m learning and applying different ETL strategies such as MT (clean–delete–insert) and RMT (clean–replace–optimize) to handle incremental and full-refresh data workflows.I also create and manage Airflow DAGs for scheduling and orchestration, monitor pipelines daily to ensure data freshness and accuracy, and troubleshoot failures caused by UI or source-side changes.Alongside data engineering, I have a strong interest in data analytics, and I enjoy working close to data to understand how technical pipelines translate into business insights.I’m continuously learning and looking to grow as a Data Engineer / Analytics Engineer, while building reliable, scalable, and production-ready data systems.

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Delphi analytics

Data Engineering & Analytics Intern

Dec 2025 – Present · 5 mos · Nagpur · On-site

Learning and contributing to ETL pipeline development by web scraping data from client native websites and multiple e-commerce platforms.
Writing and improving data extraction scripts, followed by hands-on work in data cleaning, transformation, and loading (ETL) workflows.
Gaining practical experience with different ETL strategies such as clean–delete–insert (MT) and clean–replace–insert–optimize (RMT) based on data requirements.
Creating, modifying, and monitoring Apache Airflow DAGs for scheduling, orchestration, and automation of ETL workflows.
Regularly validating data freshness, completeness, and accuracy through daily pipeline checks.
Debugging and fixing ETL failures caused by UI changes, site structure updates, or source-side issues, and learning failure-handling best practices.
Assisting in optimizing ETL pipelines to improve performance, reliability, and data quality.
Collaborating with team members to understand business requirements and end-to-end data workflows in a production environment.

Apache AirflowETL PipelinesData Engineering

Codons

Data Analyst

Oct 2024 – Apr 2025 · 6 mos · Nagpur, Maharashtra, India · On-site

As a Data Analyst Intern, I worked on multiple real-world projects that involved transforming raw data into actionable insights to support business decision-making. My responsibilities included data preparation, visualization, and deriving analytical solutions using industry-relevant tools and techniques.
Key Contributions:
Led analysis on datasets across diverse domains such as HR attrition, fleet operations, automotive trends, and retail products, focusing on uncovering patterns and business drivers.
Designed and developed interactive dashboards in Power BI, enabling clear visual representation of KPIs and trends for internal stakeholders.
Utilized SQL for structured data extraction, joins, and filtering, supporting seamless data integration from various sources.
Applied data cleaning, outlier detection, and preprocessing techniques using Python libraries (Pandas, NumPy), and visualized insights with Matplotlib and Seaborn.
Explored and implemented DAX expressions for calculated columns, measures, and advanced analytical logic in Power BI.
Contributed significantly to an HR Attrition project by identifying critical employee exit trends, enabling the team to propose retention-focused strategies backed by data.
Collaborated closely with mentors to ensure accuracy, efficiency, and business relevance in all project outcomes.
This internship provided hands-on exposure to the end-to-end data analysis process and strengthened my ability to interpret and present data-driven insights in a professional environment.