Staff Data Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Engineer based in Canada.

This role sits at the core of a high-scale data platform powering real estate intelligence, property discovery, and AI-driven workflows across millions of listings and user interactions. You will design and operate large-scale data systems that ingest, normalize, and enrich property and behavioral data from hundreds of MLS feeds and external sources. The work directly enables customer-facing experiences such as search, recommendations, and AI-assisted operations. You will operate at the intersection of backend engineering, data infrastructure, and applied AI, helping turn complex, high-volume datasets into reliable and actionable products. The environment is highly technical and collaborative, with strong emphasis on ownership, scalability, and production-grade reliability. This is a senior-level role where your architectural decisions will shape how data flows across the entire platform.

You will be responsible for designing, building, and scaling end-to-end data systems that power property intelligence, search, recommendations, and AI-driven workflows across a high-volume distributed architecture.

• Own the architecture and evolution of large-scale data pipelines, including streaming and batch systems for MLS and property data
• Design and implement event-driven data flows using Kafka or similar messaging systems
• Build and maintain backend services and APIs in Python or Java to serve data to product and AI systems
• Develop scalable data processing workflows using Spark or Flink, orchestrated with tools such as Airflow
• Ensure high standards of data quality, lineage, governance, and reliability across all pipelines
• Implement observability practices including monitoring, alerting, logging, and operational runbooks
• Collaborate with product, ML, and engineering teams to support AI agents and data-driven features
• Mentor engineers and contribute to technical design reviews and architectural decisions

Requirements:

You are an experienced senior or staff-level data engineer with strong expertise in distributed systems, data platforms, and production-grade data pipelines, ideally with exposure to AI-driven products.

• 10+ years of software engineering experience, including ownership of large-scale production systems
• Strong experience building and operating data-intensive distributed systems at scale
• Proven experience in a senior, staff, or lead engineering role influencing architecture and technical direction
• Strong programming skills in Python or Java, with experience building microservices and APIs
• Hands-on experience with Kafka or equivalent event streaming systems (e.g., Kinesis, Pub/Sub)
• Strong expertise in Spark or Flink for large-scale batch and streaming data processing
• Experience with Airflow or similar orchestration tools and Kubernetes-based environments
• Strong SQL, data modeling, and ETL/ELT design experience
• Experience with cloud platforms (AWS preferred) and understanding of cost, scalability, and reliability tradeoffs
• Experience building or integrating AI/LLM-based systems, agents, or automation workflows is highly valued
• Familiarity with tools such as LangChain, PydanticAI, or similar frameworks is a plus
• Strong communication skills with the ability to influence technical and non-technical stakeholders
• Proven ability to mentor engineers and drive best practices across teams

Benefits:

• Competitive compensation aligned with senior/staff engineering roles
• Remote-friendly work environment within Canada
• Opportunity to work on large-scale, high-impact real estate data and AI systems
• Exposure to cutting-edge AI agent and LLM-powered workflows
• Strong ownership over architecture and platform direction
• Collaborative, high-growth engineering culture
• Opportunity to work with modern data stack technologies at scale
• Career growth in a fast-scaling, well-funded tech environment
• Inclusive and innovation-driven workplace culture