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Salary: CAD 140,000 - 165,000 / annual
Altus Group is hiring a Senior Data Engineer to support Altus Labs, the company's innovation hub for commercial real estate analytics. Reporting to the Head of Data Science, you will own data pipeline architecture and platform infrastructure end-to-end, from ingestion through delivery to Data Scientists, ML Engineers, and platform services.
You will combine hands-on technical execution with thoughtful architectural decision-making to build reliable, scalable data infrastructure supporting analytics and machine learning. Working across Data Engineering, Data Science, ML Engineering, and platform teams, you will establish technical standards, improve data quality, and develop reusable tools and frameworks.
Key responsibilities include:
- Design and own batch and streaming data pipelines from ingestion through delivery, making practical decisions about data modeling, storage, and orchestration
- Build and maintain scalable data infrastructure using Databricks and cloud environments, including platform configuration, access controls, orchestration, and cataloging
- Implement data quality checks and lineage tracking to identify issues before they affect downstream models, reports, or analytical workflows
- Create reusable pipeline templates, tools, and documentation to improve consistency across the team
- Partner with Data Scientists, ML Engineers, and platform teams to understand requirements and translate them into dependable pipelines
- Contribute to code reviews, technical design discussions, and mentorship of junior engineers
- Investigate and resolve production issues independently, balancing immediate delivery with long-term scalability
This is a full-time remote position open to candidates based in Canada or the UK. You will have the opportunity to shape data architecture, influence how data is modeled and delivered, and support innovation in commercial real estate analytics.
Requirements:
- Proven experience designing, building, and operating production data pipelines and infrastructure at scale
- Strong programming skills in Python, SQL, and Spark, with solid understanding of distributed data processing
- Practical experience with Databricks and related technologies (Unity Catalog, Workflows, Delta Lake) or equivalent cloud data platforms
- Experience with pipeline orchestration and development tooling such as Databricks Asset Bundles, Airflow, or dbt
- Demonstrated ability to independently investigate production issues, make sound architectural decisions, and balance delivery with scalability
- Strong communication skills with technical and business stakeholders; comfort with code reviews, pairing, and mentoring
- Understanding of how domain context informs data modeling and analytical solution design
- Experience in finance, credit, commercial real estate, or related data domains is an asset
- Degree in Computer Science, Engineering, or related technical field is an asset; equivalent knowledge through education, training, and practical experience is valued
