Data Engineer Intern
First seen by Alion on Oct 28, 2026.
About NexGen Tech Solutions
NexGen Tech Solutions is a global IT services, AI engineering, and digital transformation company headquartered in Frisco, Texas, USA, with delivery operations across India and international markets.
The company specializes in Artificial Intelligence, Generative AI, Agentic AI, Cloud Computing, Data Engineering, Cybersecurity, and Enterprise Software Development.
Through its AI-focused platforms and engineering expertise, NexGen helps organizations design, develop, and deploy intelligent, scalable, and secure technology solutions across multiple industries.
At NexGen, we are committed to innovation, continuous learning, and developing next-generation AI-powered solutions that solve real-world business challenges.
Job Summary
We are looking for an enthusiastic and technically curious Data Engineer Intern to join our Data Engineering team.
The ideal candidate should have a strong foundation in Python, SQL, databases, and data structures, along with a basic understanding of data pipelines, ETL/ELT processes, and cloud-based data technologies.
As a Data Engineer Intern, you will work closely with experienced Data Engineers, Cloud Engineers, and Data Analysts to develop, maintain, and optimize data pipelines and support modern data platforms.
This internship offers hands-on exposure to real-world data engineering projects, data integration, cloud technologies, and big data processing frameworks.
Key Responsibilities
- Assist in designing, developing, testing, and maintaining data pipelines for structured and unstructured data.
- Support data extraction, transformation, and loading (ETL/ELT) processes from multiple data sources.
- Write and optimize SQL queries for data extraction, transformation, and analysis.
- Develop Python scripts for data processing, automation, and data integration.
- Assist with data cleaning, validation, transformation, and quality checks.
- Work with relational databases and understand data modeling concepts.
- Support the integration of data from APIs, databases, flat files, and cloud storage systems.
- Gain exposure to cloud-based data engineering services on Azure, AWS, or Google Cloud.
- Assist in troubleshooting data pipeline failures and resolving data quality issues.
- Support data warehouse and data lake development activities.
- Collaborate with Data Engineers, Analysts, and cross-functional teams to understand business and technical requirements.
- Prepare technical documentation for data pipelines, workflows, and development activities.
- Follow coding standards, version control practices, and data security guidelines.
Required Technical Skills
1. Programming
- Good understanding of Python programming.
- Familiarity with Python libraries such as Pandas and NumPy.
- Knowledge of programming fundamentals, data structures, and basic algorithms.
2. SQL & Databases
- Strong foundational knowledge of SQL.
- Understanding of joins, aggregations, subqueries, and basic query optimization.
- Familiarity with relational database systems such as MySQL, PostgreSQL, or SQL Server.
- Basic understanding of database design and normalization.
3. Data Engineering Fundamentals
- Understanding of ETL and ELT concepts.
- Basic knowledge of data pipelines and data integration.
- Familiarity with structured and semi-structured data formats such as CSV, JSON, and Parquet.
- Understanding of data cleaning, transformation, and validation techniques.
4. Development Tools
- Basic knowledge of Git and version control.
- Familiarity with Jupyter Notebook or Visual Studio Code.
- Understanding of REST APIs and data extraction methods.
Good to Have Skills
- Exposure to cloud platforms such as Microsoft Azure, AWS, or Google Cloud.
- Basic familiarity with Azure Data Factory (ADF), Azure Databricks, or Microsoft Fabric.
- Understanding of Apache Spark or PySpark.
- Awareness of data warehousing concepts and platforms such as Snowflake, Amazon Redshift, or Google BigQuery.
- Familiarity with workflow orchestration tools such as Apache Airflow.
- Basic understanding of data lakes, lakehouse architecture, and Delta Lake.
- Exposure to Power BI or other business intelligence tools.
- Basic knowledge of Linux commands and shell scripting.
- Understanding of data modeling concepts, including star and snowflake schemas.
- Familiarity with Docker and CI/CD concepts.
Educational Qualifications
- Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, or a related field.
- Strong analytical, logical reasoning, and problem-solving skills.
- Basic understanding of software development practices.
- Good written and verbal communication skills.
- Willingness to learn new technologies and work in a collaborative engineering environment.
What You Will Learn
- Develop and maintain production-oriented data pipelines under engineering supervision.
- Gain hands-on experience with Python, SQL, and modern data engineering tools.
- Understand cloud-based data architectures and ETL/ELT workflows.
- Learn how data warehouses, data lakes, and lakehouse platforms operate.
- Work with real-world datasets and business use cases.
- Understand data quality, pipeline monitoring, and performance optimization.
- Gain exposure to enterprise data engineering best practices.