Data Engineering Intern

We are looking for a Data Engineering Intern who is passionate about working with data, building scalable data pipelines and solving real-world business problems through technology.

As part of the Data/Technology team, you will work on live projects involving data ingestion, transformation, data quality, automation and analytics infrastructure across our digital-first brands and platforms.

This is a hands-on opportunity to learn how data powers D2C commerce, customer experience, supply chain, marketing and business decision-making.

What You Will Do

• Build and maintain ETL/ELT data pipelines for structured and semi-structured data.
• Write efficient SQL queries for data extraction, transformation and analysis.
• Develop data transformation and automation workflows using Python.
• Work with databases, data warehouses and cloud-based data platforms.
• Integrate data from multiple sources such as e-commerce platforms, APIs, applications and business systems.
• Perform data cleaning, validation and quality checks to ensure data accuracy.
• Support development of reusable datasets and data models for analytics and reporting.
• Troubleshoot pipeline failures and investigate data inconsistencies.
• Automate repetitive data-processing and reporting activities.
• Collaborate with Data Scientists, Analysts, Product Managers and Engineering teams.
• Explore opportunities to use AI/ML and automation to improve data engineering processes.
• Document data pipelines, processes and technical solutions.

What We're Looking For

• Currently pursuing a B.Tech/B.E./M.Tech in Computer Science, Information Technology, Data Science, Electronics or a related discipline.
• Strong understanding of SQL and Python.
• Good understanding of data structures, databases and programming fundamentals.
• Familiarity with relational databases such as MySQL/PostgreSQL is preferred.
• Basic understanding of ETL/ELT concepts and data pipelines.
• Exposure to any cloud platform such as AWS, GCP or Azure is a plus.
• Familiarity with tools such as Spark, Airflow, dbt, Kafka or Databricks is an added advantage.
• Strong problem-solving and analytical thinking skills.
• Curiosity to understand how technology and data can solve business problems.
• Ability to work independently while collaborating effectively with cross-functional teams.

Good to Have

• Academic or personal projects involving data pipelines, APIs, databases or analytics platforms.
• Experience working with Git/GitHub.
• Exposure to REST APIs and JSON.
• Understanding of data warehousing concepts.
• Participation in hackathons, coding competitions or open-source projects.