Data Engineer

The Story So Far: We're Building a Global Brand in Real EstateHuspy is one of the leading property technology companies in EMEA.Launched in ****, we now operate in multiple cities across the UAE and Spain, expanding into Saudi Arabia and 3 more European markets by ****.
Today, we own the largest portion of the UAE mortgage market and are one of the fastest-growing players in every European city we've entered.We've raised over $140 million (Series A and Series B) from the world's top investors, including Sequoia Capital and Balderton Capital, to reshape the homebuying journey through powerful technology and agent-first tools.We've built a SuperApp that empowers real estate agents and mortgage brokers, bringing cutting?edge technology to one of the world's most traditional industries.
We're transforming how property transactions happen — faster, smarter, and better for everyone.We're not slowing down.
The question is: will you be part of what's next?
The Main Event: What You'll Drive, Build, and OwnDesign and Scale Data Pipelines: Build and maintain reliable batch and streaming pipelines that connect our applications, events, and external sources to Snowflake, ensuring data flows seamlessly across our platform.Streaming Data at Scale: Work with Kafka, Schema Registry, and event-driven architectures to power real-time data products and ensure downstream systems get trustworthy, well-structured events.Pipeline Orchestration: Use Airflow to orchestrate complex workflows, automate dependencies, and ensure data availability for analytics and business processes.Data Infrastructure & Cloud Services: Leverage AWS tools (ECR, ECS, S3, etc.) to build scalable, containerized data services and optimize storage, compute, and costs.Data Quality & Observability: Implement testing frameworks, monitoring, and alerting for data pipelines to ensure reliability and trust at scale.Infrastructure as Code: Manage data infrastructure with tools like Terraform, Helmfile, or CloudFormation, automating deployments and ensuring reproducibility.Optimize for Scale and Performance: Continuously improve the throughput, latency, and cost efficiency of pipelines, ensuring the platform scales with the business.Modeling & Governance: Apply strong data modeling fundamentals (e.G., Kimball, Data Vault) and enforce governance around PII, compliance, and lifecycle management.Collaboration for Impact: Partner with analysts, business stakeholders, and product teams to translate requirements into well-designed pipelines and models that unlock business value.Automation & CI/CD: Implement testing, linting, and automated deployments for data pipelines to ensure high-quality, production-ready code.The Perfect Match: What It Takes to Succeed at HuspyProven Experience: 4+ years in a Data Engineering role (or Analytics Engineering with strong pipeline/infrastructure experience).
Python First: Proficiency in Python for ETL, orchestration, and automation.Airflow Practitioner: Hands?on experience building DAGs and managing workflows in Airflow (or equivalent orchestration tool).
Streaming & Batch Expertise: Comfort working with event streaming systems (Kafka, Schema Registry) as well as traditional batch pipelines.Cloud Native: Practical experience with AWS services (S3, ECR, ECS, IAM, etc.).
SQL & Warehousing Skills: Strong SQL and exposure to cloud warehouses (Snowflake preferred).
Modeling Mindset: Ability to design data models that balance scalability, simplicity, and business needs.Stakeholder Collaboration: Skilled at working with product, ops, and analytics teams to turn business requirements into working data solutions.Work Setup:Hybrid in Dubai or Madrid, remote anywhere in the EU.
Or we offer relocation support to Dubai or Madrid, if preferred.
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