Data Warehouse Engineer Intern

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When it comes to what you want in your career, if you can imagine it, you can do it at Parsons. Imagine a career working with intelligent, diverse people sharing a common quest. Imagine a workplace where you can be yourself. Where you can thrive. Where you can find your next, right now. We’ve got what you’re looking for.

Job Description

Position Overview

Parsons Corporation is seeking a Data Engineering Intern with an emphasis on learning and applying foundational data Engineering techniques to real-world challenges. The ideal candidate will work alongside experienced engineers and data scientists to support the development of data pipelines, assist with processing unstructured data and help maintain internal tools that support our AI-driven infrastructure initiatives. Join a dedicated and distributed team of scientists, software architects, and software engineers responsible for developing AI capabilities to expedite how engineering and construction projects are conceived and delivered.

Key Responsibilities

Unstructured Data Processing

• Assist in extracting and cleaning unstructured data such as text from Excel, PDFs, scanned documents, or logs.
• Learn to work with basic tools and scripts to prepare unstructured data for further analysis.
  
  
  

Data Pipeline Development

• Support the development of lightweight data pipelines using Python and open-source libraries (e.g., Pandas, PySpark basics).
• Contribute to automating simple data workflows and understand the basics of pipeline orchestration.
  
  
  

Data Warehousing & Storage

• Gain exposure to relational databases such as MS SQL Server, PostgreSQL or MySQL and help with basic data entry, querying, and updates.
• Storing unstructured content in NoSQL DB like MongoDB and file storage platforms.
  
  
  

Cloud Integration

• Observe and assist in using cloud-based services such as AWS S3, Azure Blob, or Google Cloud Storage for storing and retrieving datasets.
• Learn how cloud tools are used for data ingestion and transformation at a scale.
  
  
  

Performance Optimization & Troubleshooting

• Help test and debug small data processing scripts.
• Learn how to monitor script execution and report on issues or anomalies.
  
  
  

Data Governance & Security

• Understand the importance of data privacy and version control in a professional environment.
• Follow data handling guidelines to ensure confidentiality and integrity of datasets.
  
  
  

Collaboration & Documentation

• Work closely with cross-functional teams including software engineers and data scientists to understand project needs.
• Maintain clear documentation of data sources, scripts used, and key learnings for knowledge sharing.
  
  
  

Required Technical Skills

SQL

• Strong knowledge of writing queries, joins, aggregations.
  
  
  

Python or Java/Scala

• For data processing tasks (Python is most common).
  
  
  

Data Modeling

• Basic understanding of schemas, normalization, star/snowflake schema.
  
  
  

ETL Concepts

• Know what Extract, Transform, Load pipelines are and how they work.
  
  
  

Databases

• Relational: MySQL, PostgreSQL, SQL Server
• NoSQL: MongoDB, Cassandra (bonus, not always required)
  
  
  

Soft Skills

Problem-Solving Mindset

• Capable of troubleshooting complex data and system issues.
  
  
  

Communication

• Strong ability to collaborate with data analysts, scientists, and other engineers to translate business requirements into effective data solutions.
  
  
  

Documentation

• Competent in documenting data workflows, system designs, and troubleshooting steps clearly and concisely.
  
  
  

Team Collaboration

• Experience working in cross-functional teams of professionals that are located around the world.
  
  
  

Education

• Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field.
• Equivalent practical experience can compensate for formal education in some cases.
  
  
  

Certifications (Optional but Valuable)

• AWS Certified Data Analytics – Specialty
• Google Professional Data Engineer
• Microsoft Azure Data Engineer Associate
• Databricks Certified Data Engineer Associate
  
  
  

Why Join Us

• Hands-on Experience: Work on real-world infrastructure and AI use cases involving large, complex datasets.
• Mentorship: Learn from senior data engineers and AI professionals.
• Skills Development: Strengthen your understanding of data engineering, unstructured data processing, and cloud workflows.
• Career Path: Potential pathway to full-time roles based on performance and project outcomes.
  
  
  

Parsons equally employs representation at all job levels no matter the race, color, religion, sex (including pregnancy), national origin, age, disability or genetic information.

We truly invest and care about our employee’s wellbeing and provide endless growth opportunities as the sky is the limit, so aim for the stars! Imagine next and join the Parsons quest—APPLY TODAY!

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