data engineer Saanichton

Redlen Technologies

Full Time Saanichton 10.56 - 12.04 CAD Today

Job description

Company Overview

Redlen Technologies’ genesis lies in the foundational work of its Co-Founder Bob Redden who undertook a Canadian Space Agency (CSA) challenge of growing crystalline materials in microgravity on the Mir and the International Space Station (ISS).

Starting from an original team of five to over 200 employees today, Redlen has continued to innovate and improve the semiconductor crystal growth and fabrication process for its world-leading Cadmium Zinc Telluride (CZT) sensors, used in Medical Imaging, Security Imaging and Non-Destructive Testing. Redlen’s technology is enabling a quantum leap forward in medical CT scanners - equivalent in scope and scale to the leap from black and white TVs to high definition 4K LED displays – improving image resolution and diagnostic accuracy, all the while substantially reducing radiation dose.

The team has grown from 50 to 200 employees in the recent past as it has secured design wins with major Fortune 500 industry customers in the medical and security industries. It plans to grow to 400 people and double its Victoria footprint in the next few years. Redlen’s impressive technical leadership and innovation led global medical equipment leader Canon Inc. to acquire Redlen for $430M in 2021 - a huge win for the B.C. tech industry.

Redlen has received numerous awards and accolades and prides itself on being a great place to work for Science, Technology, Engineering, and Math (STEM) roles, and for being an equal opportunity employer.

Job Description:
Our R&D team plays a key role in technology delivery to OEMs for photon-counting computed tomography (PCCT). This is a dynamic role where, as a data engineer, you will also perform data scientist-level analysis.The successful applicant will assume a key and hands-on role in unlocking the information currently hidden in the gigabit-per-second image data flowing from these X-ray detectors during R&D experiments, reliability studies and production testing. You will be a bridge between this information and colleagues who have developed the world-leading Cadmium Zinc Telluride (CZT) growth technology, process development engineers, reliability engineers and application specialists all working to develop and implement our technology roadmap for detector performance, reliability and manufacturability improvements.

Duties and Responsibilities:

Develop tools to extract information from data sources used by the R&D, Validation and Test, and Manufacturing Teams, which include production and R&D databases, cloud-based data processing for production, and file-based results in some cases.
Carry out preprocessing of structured and unstructured data, including cleansing, and validating the integrity of data to be used for analysis.
Develop preprocessing tools compatible with the GB/s data flow from devices during testing, which integrate established algorithms and tools that convert raw count data into various performance metrics such as e.g., stability and uniformity maps.
Develop statistical models to help identify patterns and trends in data.
Develop appropriate predictive models and machine learning algorithms that relate data at one stage of production to outcomes at another, supports constant performance tracking and data reanalysis. Use these tools to improve and/or simplify our practices, e.g., in screening of CZT sensors before they are integrated into detectors, in reliability prediction, etc.
Interpret and present the data using advanced visualization techniques appropriate for both data science specialists and accessible formats appropriate for less specialized consumers of the information.
Write reports and make recommendations as appropriate.
Contribute to design of experiments (DOE) to isolate the factors of interest and block any confounding factors that cause process or measurement variation.
Execute additional tasks and duties as applicable.

Experience:

Proven experience in a Data Engineering, Scientist, or Analyst role.
Experience in data mining and cleaning.
Understanding of machine-learning; familiarity with operations research is a benefit.
In-depth programming experience with relevant tools, including experience with databases (SQL or NoSQL).
Working with big data in emerging applications and/or relatively small organizations.
Presentation of data using advanced visualization tools, including in written reports.
Experience in a physical science or engineering discipline is an asset.
Familiarity with process engineering tools such as Design of Experiments (DOE) and statistical data analysis using JMP or MiniTab is an asset.

Skills:

Strong programming skills and ability to learn new tools quickly.
Strong math skills (e.g., statistics, algebra).
Excellent oral and written communication and presentation skills.
Analytical mind and problem-solving aptitude.
Demonstrated positive attitude and self-motivation.
Ability to work with limited supervision and manage responsibilities to all project stakeholders in a proactive way.
Outstanding interpersonal skills and ability to work in a team environment.

Personal Characteristics:

Hands-on.
Attention to detail.
Quality-oriented.
Collaborative.
Time sensitive.
Customer-focused.
Flexible.
Curious.
Willing to learn.

Education:
Master’s degree or higher in engineering physics, applied physics, physics, electrical engineering, computer engineering, computer science, applied mathematics or relevant field.