Data Engineering Scientist

Maya Heat Transfer Technologies; Montreal; Hybrid; CAD 70,000 - 110,000; Full time

Job summary

Join a forward-thinking company as a Data Engineering Scientist, where you'll revolutionize industrial operations through innovative data pipelines. Collaborate with experts in engineering and manufacturing to transform complex sensor data into actionable insights, enhancing decision-making processes. With a focus on AI and machine learning, this role offers a unique opportunity to work hands-on with cutting-edge technology in a dynamic environment. Enjoy flexible working hours, a competitive salary, and comprehensive benefits from day one. Your passion for data and problem-solving will help shape the future of industrial AI.

Benefits

Flex Working Hours

100% Employer-Paid Benefits

Career Growth Opportunities

Learning Opportunities

Generous Time-Off Policy

Structured Onboarding Program

Qualifications

• Strong understanding of data engineering and mining techniques.
• Experience with timeseries databases and industrial sensor data.

Responsibilities

• Collaborate with data scientists to create effective data pipelines.
• Ensure data quality and cleanliness for reliable ML-Ops operations.

Skills

Data Engineering

Data Mining

Statistical Modeling

Python Scripting

SQL

Data Visualization

Teamwork Skills

Education

Bachelor's Degree

Master's Degree

PhD

Tools

OSIsoft Aveva PI

Azure IoT

Timeseries Database

NoSQL Databases

Job description

Maya HTT is a world leading developer of digital industries software solutions. The world’s top tier engineering and manufacturing organizations rely on Maya HTT’s experience and expertise to achieve the full potential of their software investment. Maya HTT is at the forefront of innovation technology. Our team delivers extensive engineering and CAE simulation expertise along with cutting-edge digitalization solutions, such as AI, machine learning, IIoT, operational technologies, and Industry 4.0.

As a Data Engineering Scientist, you will help revolutionize industrial operations by building scalable data pipelines that power cutting-edge industrial AI solutions. You'll work closely with industrial data scientists, engineers, and manufacturing experts to unlock insights from operational tech (OT) data—sensor streams, video, audio, and more. You'll be the bridge between raw data and real-world impact: designing secure, reliable pipelines that fuel machine learning, deep learning, and advanced analytics. Your mission? Turn complex, high-frequency industrial data into actionable intelligence for smarter decision-making. If you love working hands-on with time-series sensor data, streaming video and audio, and thrive in a friendly and agile environment, we want you on our team! Experience with AI-Ops/ML-Ops systems is a big plus. Bring your passion for data, innovation, and problem-solving to Maya HTT—and help shape the future of industrial AI, engineering and manufacturing!

What to expect as your main responsibilities:

• Collaborating with data scientists to create the right data pipelines
• Ensuring the data engineering is done properly while remaining agile in the gradual data validation, data merging, and in general produce the right data aligned to the business use case to solve
• Defining the data quality metrics to be tracked from a business perspective, and metrics to be optimized on
• Checking data cleanliness and identifying dataset biases whenever relevant
• Experimenting, building, and optimizing selected data pipeline and methods
• Leveraging data mining to uncover interesting patterns or correlation using state-of-the-art methods to help data scientists and subject matter experts
• Augmenting datasets either algorithmically or using third party sources of information when needed
• Enhancing data collection procedures to include information that is relevant for building better engineering and manufacturing automation & optimization systems
• Interacting with data engineering specialist to ensure data processing, cleansing, and verifying the integrity of data used for the ML-Ops is reliably done and available during 24/7 operations
• Presenting data mining and early data finding results in a clear manner
• Collaborating with 24/7/365 ML-Ops team and ensuring the tracking of data feeding the ML/AI model performance over time

Minimum Requirements:

• A Bachelor, Master degree or PhD
• Excellent understanding of data engineering, data mining, and statistical modeling
• Experience with common data engineering toolkits such as ex-OSIsoft Aveva PI, or Insights Hub, or Azure IoT
• Experience with timeseries database is a big plus, especially if you have hands-on experience with industrial sensors data
• Excellent scripting skills (typically python, SQL)
• Good data story communication skills is a big plus
• Experience with data visualisation tools
• Experience using query languages such as SQL
• Experience with NoSQL databases
• Good teamwork skills

Why join Maya HTT?

• Flex Working Hours and Hybrid Work.Office downtown Montreal, 2-minute walk from Atwater Metro.
• Permanent Position andCompetitive Base Salary.
• 100% Employer-Paid Benefits starting from Day One:Medical, Dental, Vision, Life, Short/Long Term disability insurances.
• Retirement Savings:Group RRSP / DPSP Plan with Employer Contributions open to join from Day One
• Career Growth Opportunities:Our flexible career paths allow you to grow, and we like to promote internally.
• Learning Opportunities:Learn from the best in the industry and develop your skills.
• Generous Time-Off Policy:We promote a Healthy Work-Life Balance with a Flexible PTO Policy, Sick/Personal Days, and a Summer Flex Schedule.
• Structured Onboarding Program:We’re invested in your success; you’ll have team members to support you and provide a wide range of assistance from Day One.
• Join an award-winning company that is recognized worldwide as an industry leader.

Our Candidate Experience Flow:HR Phone Screen - Virtual Interviews using Microsoft Teams - Job Offer

Maya HTT is an equal opportunity employer and committed to fostering diversity and inclusion in the workplace. Accommodations are available upon request for candidates taking part in all aspects of the hiring and selection process.