Manager, Data Engineering & Governance

We're hiring a Principal Process Development Engineer to work with industrial customers to support the deployment of AI-driven solutions in technical and operational environments.This is a cross-functional role that combines engineering, customer collaboration, data analysis, and technical problem-solving. You'll work with a range of stakeholders to understand operational challenges, analyze process and production data, develop models and workflows, and help drive improvements using the company's platform.
CA$120,000.00–CA$135,000.00 yearly
Full-time
At GroupHEALTH, we’re proud of the work we do, but it’s how we do it that truly sets us apart.We’re a fast-moving, ever-evolving, stable organization with deep roots and a bold vision: to transform...
Permanent
Every day, ANDRITZ continues to deliver successful innovative solutions to our customers globally.Why are we so successful? Because we are passionate and love what we do! We are at the forefront of...
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We're hiring a Principal Process Development Engineer to work with industrial customers to support the deployment of AI-driven solutions in technical and operational environments.
This is a cross-functional role that combines engineering, customer collaboration, data analysis, and technical problem-solving. You'll work with a range of stakeholders to understand operational challenges, analyze process and production data, develop models and workflows, and help drive improvements using the company's platform.
The ideal candidate is comfortable engaging with technical teams, working with data and analytical tools, and translating technical findings into practical business outcomes.
Internally, you'll act as a technical subject matter expert and advocate for customer needs across manufacturing and process-related initiatives.
Externally, you'll support enterprise customers by partnering with engineering and operations teams to maximize value from the platform, whether by improving existing workflows or helping implement new solutions.
In collaboration with Sales, Product, and Engineering, you'll also contribute to identifying new use cases and shaping future platform capabilities.
What You'll Do
Partner with customers to support deployment and adoption of platform solutions
Lead onboarding and implementation efforts across technical and operational environments
Build relationships with engineering, operations, and leadership stakeholders
Identify opportunities for operational improvement and data-driven insights
Translate customer challenges into actionable technical solutions and product feedback
Support projects from discovery through implementation and impact measurement
Technical Analysis & Problem Solving
Analyze operational and process datasets to identify trends, bottlenecks, and optimization opportunities
Develop analytical models, simulations, and workflows using Python and related tools
Work with industrial data systems and manufacturing datasets
Collaborate with product and engineering teams to improve platform functionality
Communicate technical findings to both technical and non-technical audiences
Support troubleshooting and continuous improvement initiatives in complex operational settings
What You'll Need
5-7 years of experience in manufacturing, process engineering, or related industrial environments
Experience developing and applying first-principles (physics-, chemistry-, and biology-based) models of bioprocesses and biologics manufacturing operations. Candidates should have demonstrated experience building mechanistic models from fundamental transport, reaction, thermodynamic, kinetic, and cellular processes rather than purely empirical or machine-learning approaches.
Examples may include:
Upstream bioprocess modeling (cell culture, microbial fermentation, metabolic and growth kinetics, nutrient consumption, product formation)
Downstream process modeling (chromatography, filtration, UF/DF, precipitation, mixing, mass transfer, adsorption, and purification operations)
Digital twins and process simulations for biologics manufacturing facilities
Scale-up and scale-down modeling based on transport phenomena and bioprocess fundamentals
Mechanistic modeling for process optimization, control, technology transfer, capacity planning, or process development
Preferred qualifications:
Experience implementing models in MATLAB, Python, gPROMS, Aspen Custom Modeler, COMSOL, Julia, or similar platforms
Experience supporting commercial manufacturing, process development, or manufacturing science and technology (MSAT) teams
Ability to derive, calibrate, validate, and interpret mechanistic models using experimental and manufacturing data
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