Data Engineering Scientist

🔥 15 hours ago

🇨🇦 Canada – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Maya HTT

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 1982

🤝 B2B

☁️ SaaS

🏭 Manufacturing

B2B • SaaS • Manufacturing

Maya HTT is an engineering software and services company that develops CAE and simulation-driven engineering tools, industrial AI, digital automation, and PLM/IoT solutions for complex engineering and manufacturing problems. With 40+ years of expertise and a portfolio that includes thermal simulation, Simcenter integrations, PCB and electronics cooling tools, SDKs for CAE translators and visualization, and an industrial AI chatbot (M-Bot), Maya HTT supplies software products, licensed partner solutions, and professional services (software development, digital services, training) to large aerospace, electronics, transportation and manufacturing customers. The company emphasizes deterministic, enterprise-grade AI for engineering, cloud-native solvers and orchestration, and services that support digital transformation across the product lifecycle.

📋 Description

• Collaborate with data scientists and engineering, manufacturing, and operations subject matter experts • Create and architect data pipelines feeding ML-Ops systems • Align, securely access, transform, merge, and fuse operational technology, historian, industrial sensor, video, and audio data • Pre-process data at the appropriate frequency for AI technologies • Build data pipelines and design experiments in an agile fashion • Work with Aveva PI AF, EF, and other PI tools • Ensure data validation, data merging, and data engineering align with business use cases • Define and optimize business-focused data quality metrics • Check data cleanliness and identify dataset biases • Experiment, build, and optimize data pipelines and methods • Use data mining to uncover patterns and correlations • Augment datasets algorithmically or with third-party information • Enhance data collection procedures for engineering and manufacturing automation and optimization systems • Coordinate with data engineering specialists to ensure reliable data processing, cleansing, integrity, and availability during 24/7 operations • Present data mining and early data findings clearly • Collaborate with the 24/7/365 ML-Ops team and track data feeding ML/AI model performance over time • Integrate time-series data into geo-spatial tools

🎯 Requirements

• A Bachelor, Master degree or PhD • Excellent understanding of data engineering, data mining, and statistical modelling • Experience with common data engineering toolkits such as ex-OSIsoft Aveva PI (a must have), Insights Hub, Azure IoT, AWS IIoT/Sitewise • Experience with geo-spatial toolkits such as Esri ArcGIS is a plus • Experience with timeseries databases, especially hands-on experience with industrial sensors data • Excellent scripting skills, typically Python, SQL, and PowerShell • Experience with cloud hosting and solutions, including Aveva and AWS • 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 • Authorization to work in the country where the job is located

🏖️ Benefits

• Permanent Position and Competitive Base Salary • 100% Employer-Paid Benefits starting from Day One: Medical, Dental, Vision, Life, Short/Long Term disability insurances • Group RRSP / DPSP Plan with Employer Contributions open to join from Day One • Career Growth Opportunities • Learning Opportunities • Flexible PTO Policy • Sick/Personal Days • Summer Flex Schedule • Structured Onboarding Program • Team support and assistance from Day One • Virtual interviews using Microsoft Teams