Guesty is the all-in-one platform helping hospitality businesses around the world automate, optimize, and scale their operations. We’re a fast-growing global startup that’s transforming how the industry works — from guest experience to business growth.
With a powerful suite of features and integrations with 150+ industry partners — including Airbnb, Vrbo, Booking.com, Expedia, Google Travel, and many more — Guesty empowers property managers to deliver top-tier guest experiences while running more efficient, data-driven operations.
We’re proud to have over 900+ team members across 16 countries worldwide, all working together to build the future of hospitality technology.
If you’re looking to grow your career in a dynamic, global, and impact-driven environment, we’d love to hear from you.
We’re looking for a talented and highly motivated Data Engineer to join our dynamic team.
The ideal candidate is a strong team player who can also take ownership, leading the design, development, and maintenance of scalable data pipelines and analytical solutions to drive our business forward.
This role is diverse and hands-on: you’ll develop and maintain cloud-based infrastructure, implement CI/CD workflows for data, and ensure clean, reliable data flows into our data warehouse. Beyond engineering, you’ll collaborate across teams and apply analytical skills to embed business logic into our pipelines, enabling the company to make data-driven decisions with confidence.
In this role, you’ll have the opportunity to work on Rentals United, our Channel Manager product. Rentals United is one of the technology leaders in the vacation rentals space, providing an advanced distribution platform for professional short-term rental property managers worldwide. The platform connects property managers to multiple global booking channels in real time, serving as a hub with integrations ranging from OTAs and sales channels to PMSes, including a White Label distribution solution. Since 2014, Rentals United has grown from preventing overbookings to becoming a strategic partner for top STR professionals, helping them execute their sales strategies across the most important channels.
Requirements:
- 2+ years of experience working as a Data Engineer.
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Strong coding skills in Python and SQL, with a focus on clean, testable, production-grade code.
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Proven experience building data pipelines with Airflow.
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Experience with analytics Databases such as BigQuery and Snowflake.
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Experience working in a cloud environment (GCP, AWS, Azure).
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Solid understanding of data modeling, database design, and performance optimization.
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Experience working in production-grade environments.
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Strong problem-solving and analytical abilities.
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Excellent communication and collaboration skills.
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Experience with modern CI/CD, observability, and infrastructure-as-code practices in the cloud.
Advantage:
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Familiarity with Kubernetes, Docker, and Terraform.
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Experience with AWS Glue.
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Exposure to implementing AI/ML capabilities in data workflows.
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Familiarity with AI coding assistants/IDEs (e.g., Cursor, Claude Code, Copilot) to accelerate development and improve efficiency.
Guesty is proud to be an Equal Opportunity Employer. We provide equal employment opportunities to all employees and applicants regardless of race, color, religion, sex, age, national origin, disability, veteran status, pregnancy, sexual orientation, or any other characteristic protected by law.
Responsibilities:
- Own the data development process end-to-end, including business understanding, methodology, QA, and maintenance.
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Design, build, and maintain scalable data systems including data lakes, warehouses, and pipelines.
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Consolidate diverse data sources (CRMs, APIs, databases, SaaS platforms) into a unified source of truth.
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Implement and manage CI/CD, observability, and infrastructure-as-code practices in a cloud environment.
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Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment
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Collaborate with product and engineering teams to identify opportunities for GenAI = across Unit's platform and processes, understand team-specific domains, and embed agents directly into existing business workflows.
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Build frameworks and internal tooling that empower other teams to adopt GenAI safely and efficiently.
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Optimize data infrastructure performance and cost, with emphasis on BigQuery optimization.
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Support Data Quality: Optimize ETL processes to handle large volumes of data while ensuring data quality and integrity across all our data sources.
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Ensure data quality and integrity across large-scale ETL processes.
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Collaborate with analysts, data scientists, and product managers to support analytics, data modeling, and governance.
