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Jobs/Data Engineer Role/luxurypresence - Sr. Data Engineer - CANADA (Remote)
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luxurypresence

luxurypresence - Sr. Data Engineer - CANADA (Remote)

Remote - Canada3d ago
RemoteSeniorNACloud ComputingSoftwareData EngineerConciergeFounderClaudeKafkaPythonTypeScriptAWS

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Requirements

• You already build with AI daily. You use Claude Code as a core part of your workflow, not as a novelty • You have strong opinions, loosely held, about how AI changes software architecture, team structure, and engineering culture • You think in systems. You connect technical decisions to customer outcomes and long-term business value • You communicate clearly and directly. You can explain complex tradeoffs to product, design, and executive stakeholders • You're energized by ambiguity and speed. You thrive in a fast-growing company where the roadmap evolves and ownership is real • You like to have fun at work. We take our craft seriously, but we don't take ourselves too seriously. We celebrate wins, crack jokes, and genuinely enjoy building together • 6+ years of professional data engineering or software engineering experience • Strong experience with distributed data processing and streaming systems (Spark / PySpark, Kafka) • Proficiency in Python (Pydantic preferred) and familiarity with Node/TypeScript is a plus • Experience building and maintaining data pipelines on AWS using tools like Airflow, Spark Streaming, and Iceberg • Solid understanding of data modeling and working with large-scale datasets • Familiarity with event-driven systems and ingestion patterns (Kafka, SQS) • Experience implementing data quality checks, monitoring, and debugging data issues • Interest in applying AI/ML or automation to improve data workflows is a plus • Proven track record leading high-impact initiatives from concept through production in a SaaS environment • Expert-level grasp of software design principles and experience with multi-tenant platform architectures • Backend: Python, PySpark, Pydantic, Node/TypeScript • Data: Iceberg, Postgres • Infrastructure: AWS, Kubernetes, Airflow, Spark Streaming • Messaging: Kafka, SQS • The real estate industry is in the midst of a seismic shift, and the future belongs to those who break new ground. As one of the fastest-growing companies in the proptech and marketing sectors, Luxury Presence challenges the status quo of what technology can do for real estate agents, leaders, and brokerages. • We're a team of agile and tenacious innovators working collaboratively to drive the industry forward. Together, we build game-changing products that empower modern real estate entrepreneurs to dominate their markets. From award-winning web design to agile SEO solutions to cutting-edge AI tools, we deliver tech that anticipates market shifts and keeps our clients ahead of their competition. • Founded in 2016 by Stanford Business School alum Malte Kramer, Luxury Presence has grown to a global team ranked on the Inc. 5000 fastest-growing companies list three years in a row. We're backed by world-class investors, including Bessemer Venture Partners, NextEquity Partners, Toba Capital, and Switch Ventures, and have raised $89 million to date. • More than 18,000 real estate businesses rely on our platform, including 30% of the Wall Street Journal RealTrends top agents and teams. Additionally, many of the industry's most powerful brokerages rely on Luxury Presence as a trusted business partner. • Every year since 2020, Luxury Presence has ranked on BuiltIn's Best Place to Work lists. HousingWire named our founder and CEO a 2024 Tech Trendsetter, we've received several Tech100 Awards, and we just scored an Inman Innovation Award for Best AI-Powered Platform.

Responsibilities

• Build and scale high-throughput streaming pipelines. Design, implement, and operate pipelines ingesting 400M+ monthly MLS updates across 350+ integrations using Airflow, Spark Streaming, Kafka, and Iceberg—ensuring reliability, performance, and data correctness. • Model and deliver high-quality, production-grade real estate datasets. Develop and maintain datasets that power core product experiences, with a focus on data modeling, transformation logic, and balancing freshness, accuracy, and cost. • Strengthen data quality and observability. Implement and improve data quality checks, monitoring, and alerting to detect issues early and reduce downstream impact. • Leverage AI to improve data operations. Contribute to AI-driven tooling that helps triage, debug, and resolve data quality issues, increasing team efficiency and reducing manual intervention.

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