Data Engineering Intern

Qeexo, Co.San Clemente, CA

About The Position

The Data Engineering Intern supports the development of scalable data systems and infrastructure that power our machine learning–based equipment monitoring platform. In this role, the intern will work with large-scale sensor datasets, cloud-based technologies, and modern data pipelines, while collaborating closely with software and machine learning engineers to enable advanced analytics and AI applications. This internship provides hands-on experience in building production-ready data systems within a fast-paced, innovative environment.

Requirements

  • Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field
  • Hands-on experience with Python and SQL
  • Exposure to data pipelines, ETL/ELT processes, or data warehousing concepts
  • Familiarity with relational and/or analytical databases (e.g., PostgreSQL, MySQL, Redshift)
  • Exposure to cloud platforms, preferably AWS
  • Strong foundation in Python programming and SQL/database fundamentals
  • Basic understanding of data engineering concepts, including pipelines, transformation, and storage
  • Familiarity with cloud computing and distributed systems
  • Analytical mindset with strong problem-solving capabilities
  • Ability to quickly learn new tools, technologies, and frameworks
  • Strong attention to detail and commitment to data accuracy and quality
  • Effective communication skills, both written and verbal
  • Ability to collaborate in cross-functional team environments

Nice To Haves

  • Experience with workflow orchestration tools (e.g., Apache Airflow)
  • Familiarity with AWS services such as S3, Lambda, Glue, or Redshift
  • Exposure to Docker, Linux, or shell scripting
  • Understanding of OLTP vs. OLAP systems
  • Experience with data lakes, data warehousing, or analytics platforms
  • Interest in machine learning and data-driven systems
  • Experience with Git or version control systems

Responsibilities

  • Build, maintain, and optimize ETL/ELT pipelines for processing sensor and operational data
  • Develop data workflows and automation using Python, SQL, and AWS services
  • Support data ingestion, transformation, validation, and monitoring processes
  • Work with structured and semi-structured data from cloud and edge-based systems
  • Collaborate with software and ML engineers to prepare datasets for analytics and machine learning models
  • Assist with integration and optimization of OLTP and OLAP systems
  • Troubleshoot pipeline issues and contribute to improvements in data reliability and performance
  • Create and maintain documentation, including data flows, system diagrams, and technical specifications
  • Participate in code reviews and adhere to engineering best practices
  • Support initiatives to improve data quality, observability, and operational efficiency
  • Contribute to continuous improvement of data infrastructure and workflows
  • Perform other related duties and ad hoc projects as assigned to support departmental and organizational goals.
  • Maintain awareness of and follow all workplace safety guidelines and promote a culture of well-being.
  • Ensure work is performed in accordance with established quality control and assurance processes.
  • Adhere to the company’s Values and Code of Conduct and uphold the highest standards of honesty, integrity, and ethical behavior in all business activities.
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