Why Keyrus, Why Now!

Keyrus is an international group of 2,800 consultants and experts across 28 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does. For more than 30 years, we have been building the data foundations that make intelligent systems work — designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value: we operationalise intelligence.

AI does not replace humans. It repositions us to a place no system can follow: understanding, deciding, designing, and creating. At Keyrus, you will not just develop skills—you will develop judgment. Your expertise sharpens with every data platform you architect, every pipeline you optimize, and every client challenge you solve.

Over time, you grow into one of the rarest professionals of the intelligence era: someone who bridges data engineering, cloud platforms, machine learning, and business decision-making at scale. This is not a role you fill. It is a discipline you master and a story you help write to become a Keyrus Architect of Intelligence.

Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.

🚀 What You'll Architect

As a Senior Data Engineer – Databricks, you will architect modern data platforms that power enterprise analytics, machine learning, and AI initiatives. You will combine deep hands-on engineering expertise with consulting leadership, designing scalable lakehouse solutions while mentoring teams and driving engineering excellence across complex client engagements.

• Lead the design, development, and optimization of Databricks-based data platforms supporting analytics, data science, and machine learning workloads

• Architect scalable lakehouse solutions using medallion architecture principles to ensure governance, performance, quality, and long-term maintainability

• Design and implement parameterized ingestion frameworks supporting batch and near real-time data processing

• Build, operate, and optimize CI/CD pipelines that enable reliable and automated deployments across environments

• Define and promote Databricks engineering standards, leveraging Feature Store, MLflow, Model Registry, Unity Catalog, and Databricks Asset Bundles (DAB)

• Lead technical discussions and mentor engineering teams, promoting best practices and high-quality implementations

• Assess existing data platforms and identify opportunities to improve performance, cost efficiency, security, scalability, and maintainability

• Collaborate closely with Solution Architects, Data Scientists, Engineers, and business stakeholders to deliver enterprise-grade solutions

• Communicate architectural decisions and technical recommendations confidently to both technical and executive audiences

• Continuously evaluate emerging Databricks capabilities and modern data engineering practices to strengthen client solutions and delivery standards

🧠 Who You Are

• You see data engineering as the foundation for scalable analytics and intelligent organizations

• You combine deep technical expertise with a consultative mindset and collaborative leadership style

• You naturally mentor others while maintaining a strong hands-on engineering approach

• You enjoy solving complex technical challenges and designing reusable, scalable architectures

• You are comfortable engaging directly with clients and influencing technical decisions with confidence

• You continuously explore new technologies and proactively improve engineering practices

• You thrive in fast-paced consulting environments where innovation and business impact go hand in hand

🛠️ What You Bring

Qualifications / Certifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field—or equivalent professional experience

• 8+ years of experience in Data Engineering, Cloud Data Platforms, or Modern Analytics environments

• Proven experience delivering end-to-end enterprise data solutions using Databricks

• Databricks, Azure, AWS, or cloud architecture certifications are considered an asset

• Native-level or fully fluent English is required; French is a strong advantage

Technical Skills

• Advanced hands-on expertise with Databricks, including Feature Store, MLflow, Unity Catalog, Model Registry, and Databricks Asset Bundles (DAB)

• Strong experience designing and implementing medallion lakehouse architectures

• Experience building parameterized ingestion frameworks for batch and near real-time data pipelines

• Proven ability to design, implement, and maintain CI/CD pipelines for Data Engineering and Machine Learning solutions

• Experience deploying Machine Learning workflows into production environments

• Deep understanding of modern data engineering patterns, cloud-native architectures, and enterprise analytics platforms

• Strong technical leadership capabilities with experience mentoring Data Engineers and ML Engineering teams

• Excellent communication skills with the ability to explain complex technical concepts to both technical and business stakeholders

⭐ Nice-to-haves

• Experience working within technology consulting or enterprise client-facing environments

• Advanced expertise with Apache Spark and PySpark performance optimization

• Experience with cloud ecosystems such as Azure, AWS, or GCP and their associated data services

• Familiarity with orchestration and transformation tools such as dbt, Airflow, or equivalent

• Experience with MLOps, Data Governance, security, and distributed data platforms

• Proactive mindset focused on innovation, continuous improvement, and adoption of evolving Databricks capabilities

🎯 What Makes You Successful

• Exceptional communication skills, with the ability to influence technical teams and business stakeholders alike

• Comfortable leading architecture discussions, mentoring engineers, and driving technical excellence

• Brings a consultative mindset that balances engineering quality with measurable business outcomes

• Demonstrates ownership, structured thinking, and strong technical judgment across the full data lifecycle

• Builds trust through collaboration, mentorship, and delivery of scalable enterprise solutions

• Thrives in environments where continuous learning and innovation are part of everyday work

Role Details

📍 Location: Hybrid – Toronto or Montreal, Canada
💼 Contract: Full-time
🌐 Work Model: Hybrid (2 days per week on site)
🚀 Level: Senior

The expected base compensation for this position ranges from $105,000 to $110,000 CAD, depending on experience, skills, location, and internal equity. This salary range is provided as a guideline and may be adjusted for the selected candidate.

Rewards - What We Offer at Keyrus

• A stimulating environment where you will be able to surpass yourself and discover new horizons

• A strong culture of innovation and entrepreneurship

• Team celebrations, social events, birthdays, breakfasts, and special activities

• Group insurance for you and your family members

• RRSP and DPSP participation plans

• Monthly Wellness Allowance

• Telecommunication reimbursement

• Flexible work-from-home policy

• 4 weeks of paid vacation

• Language courses (French & English)

• Access to continuous learning through conferences, certifications, training programs, and industry events

🌍 What We Stand For

• Collective Intelligence — Collaboration across expertise, functions, and geographies makes it possible to combine know-how and deliver more comprehensive responses to client challenges.

• Reliability — The ability to deliver complex projects with rigour is one of the pillars of our client relationship.

• Pragmatism — Prioritising concrete impact and measurable value over abstract technological discourse.

• Entrepreneurial Spirit — Curiosity, energy, and freedom are the foundations of our culture; they enable initiative and sustained innovation.

ABOUT KEYRUS

At Keyrus, we help organizations move from experimental AI to industrialized AI, from isolated agents to orchestrated systems, and from insight to execution. This is the discipline we call being an Architect of Intelligence. Designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value: we operationalize intelligence.

Powered by our proprietary Human Orchestrated Model™ (HOM), we architect reliable:

• Intelligence Foundations

• Human in Command governance

• Performance Steering

To create intelligent environments where technology amplifies human capabilities and performance compounds over time.

With 30+ years of expertise and 2,800 employees across 28 countries, we help organizations go beyond transformation: to build adaptive, resilient, and continuously improving intelligent organizations.

AI does not transform businesses. Architected intelligence does.

Keyrus is listed on Euronext Growth Paris. (ALKEY – ISIN Code: FR0004029411 – Reuters: KEYR.PA – Bloomberg: ALKEY: FP).

For more information: www.keyrus.com