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Staff Data Engineer

Job Description - 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.


Accountabilities:


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


How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!


 

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

 

 

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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