Data Engineering Intern

Valid8 Financial, Inc.; San Clemente (CA); On-site; USD 27,552 - 48,216; Full time

Job summary

Valid8 Financial, Inc. in San Clemente, CA, is seeking a Data Engineering Intern to support the development of scalable data systems for machine learning-based monitoring platforms. The role involves working with large-scale sensor datasets and cloud-based technologies in a fast-paced, innovative environment.

Interns will gain hands-on experience with data workflows, automation, and collaboration with engineering teams. Applicants should be pursuing a relevant technical degree and have foundational skills in Python and SQL.

Qualifications

• Currently pursuing a Bachelor's or Master's degree in a related technical field.
• Hands‑on experience with Python and SQL.
• Exposure to data pipelines, ETL/ELT processes, or data warehousing concepts.

Responsibilities

• Build, maintain, and optimize ETL/ELT pipelines for processing sensor and operational data.
• Collaborate with software and ML engineers to prepare datasets for analytics and machine learning models.
• Create and maintain documentation for data flows and system diagrams.

Skills

Python programming

SQL/database fundamentals

Data engineering concepts

Problem-solving capabilities

Effective communication

Education

Pursuing Bachelor's or Master's degree in related technical field

Tools

AWS services (S3, Lambda, Glue, Redshift)

PostgreSQL or MySQL

Workflow orchestration tools (Apache Airflow)

Job description

TDK SensEI is transforming how sensor data is collected, processed, and leveraged powering intelligent, data-driven decision-making across industrial environments. As a pioneer in automated machine learning for edge devices and a subsidiary of TDK Corporation, a global leader in sensor technology, SensEI operates at the forefront of industrial AI and analytics.

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.

Key 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

Additional Responsibilities

• 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

Other Duties

• 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

Qualifications

Education / Experience

• Currently pursuing a Bachelor’s or Master’s degree in 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

Knowledge, Skills, and Abilities

• 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

Preferred / Bonus Qualifications

• 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