Data Engineer (Teradyne, Costa Rica)
Confirmed on the employer's own hiring board on Nov 4, 2026. First seen by Alion on Sep 24, 2026. Teradyne scores A on the Alion truth index.
We are the global test and automation specialists, powering next-generation technologies through sophisticated solutions. Behind every electronic device you use, Teradyne's test technology ensures your device works right the first time, every time! Our portfolio of automation solutions help manufacturers to develop and deliver products quickly, efficiently and cost-effectively. Together, Teradyne companies deliver manufacturing automation across industries and applications around the world!
We attract, develop, and retain a high-performance workforce, comprised of people with diverse backgrounds and a shared drive for excellence. We strive to foster a positive and inclusive work environment that helps employees, and communities, thrive.
Our Purpose
At Teradyne, we bring together experience and innovation to drive excellence in every connection. We value diversity of thought and create an environment where all employees feel included, supported, and encouraged to contribute. We believe different perspectives strengthen our teams, enhance decision-making, and enable better outcomes.
Opportunity Overview
As a Data / AI Engineer, you will help design and develop data, analytics, and AI solutions that support informed decision-making across Manufacturing, Test, and Operations organizations.
This role brings together data engineering, analytics, and applied AI into a comprehensive engineering scope. You will contribute to building data pipelines, analytics capabilities, and machine learning solutions that transform operational data into clear and actionable insights.
You will collaborate with cross-functional teams to translate operational challenges into scalable data and AI solutions that improve visibility, quality, and decision efficiency across the organization.
All About You
We seek individuals who share our passion and determination. Our commitment to customer success drives us to go the extra mile. If you’re ready to join us in this mission, take a closer look at the minimum criteria for the position.
Responsibilities
- Design, build, and maintain scalable data pipelines to process manufacturing, test, and operational data
- Establish and support data schemas, logging practices, and data quality processes to enable reliable analytics and AI applications
- Develop analytics-ready datasets and reporting layers to support operational monitoring and decision-making
- Build and maintain dashboards and self-service analytics tools using SQL and BI platforms (e.g., Power BI)
- Collaborate with Operations and Engineering teams to understand requirements and deliver sustainable data solutions
- Contribute to the development of pipelines for training, evaluating, and deploying machine learning models
- Apply machine learning techniques to use cases such as anomaly detection, pattern recognition, and predictive insights
- Support the definition of evaluation metrics, validation approaches, and monitoring strategies to ensure solutions provide value.
Required Qualifications
- B.S. in Computer Science, Computer Engineering, or a closely related field, or equivalent practical experience.
- English Proficiency
- 3 years of experience in
- delivering production-quality data solutions and/or applied ML systems
- Python for data processing, analytics, and AI workflows.
- SQL skills for querying, transforming, and analyzing large datasets.
- Programming languages commonly used in data or platform environments (e.g., C#, Java, Scala, or similar).
- Software engineering fundamentals such as readable code, version control, and testing practices.
Preferred Qualifications
- Experience working with manufacturing, test, or operational data.
- Familiarity with modern data platforms such as Microsoft Azure and/or Snowflake.
- Experience supporting BI or analytics platforms (e.g., Power BI).
- Exposure to production ML systems (deployment, monitoring, MLOps concepts).
- Experience with advanced ML approaches such as graph-based modeling, optimization techniques, or reinforcement learning is a plus.
The ideal candidate will have the following behavioral traits
- Strong attention to detail and analytical/problem-solving skills
- Great communication skills