What You'll ArchitectAs 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 BringQualifications / 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
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Contract: Full-time
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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
