What are the responsibilities and job description for the Data Engineering Intern position at ARM, Inc.?
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.
Workplace Safety: Maintain awareness of and follow all workplace safety guidelines and promote a culture of well-being.
Quality and Compliance: Ensure work is performed in accordance with established quality control and assurance processes.
Ethics and Integrity: 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:
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
Knowledge/Skills/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
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.
Workplace Safety: Maintain awareness of and follow all workplace safety guidelines and promote a culture of well-being.
Quality and Compliance: Ensure work is performed in accordance with established quality control and assurance processes.
Ethics and Integrity: 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:
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
Knowledge/Skills/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