Mploy - דרושים

דרושים Data Engineer בתל אביב

 

20/11/2025

 תל אביב

 Guesty

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 versatile, talented, and highly motivated Data Engineer to join our growing team.

If you’re passionate about solving complex problems, thrive in dynamic environments, and love working at the intersection of data engineering, machine learning infrastructure, and AI innovation, this role is for you.

As a Data Engineer, you’ll play a key role in shaping how data flows through the company, from building scalable pipelines and robust infrastructure to powering data science models and enabling internal teams with intelligent GenAI-powered tools. This is a hands-on, high-impact role with plenty of room for ownership, creativity, and growth.

This is a high-impact role where your work will shape how the company leverages data and AI. If you want to build, innovate, and push boundaries in a collaborative and fast-moving environment, we’d love to meet you.

Responsibilities:

  • Own the entire data lifecycle from understanding business needs and building reliable pipelines to ensuring data quality, observability, and performance.
  • Design, build, and scale modern data infrastructure including data lakes, warehouses, and complex ETL/ELT pipelines.
  • Integrate and consolidate diverse data sources (CRMs, APIs, databases, SaaS platforms) into a single, trusted source of truth.
  • Implement and manage CI/CD, observability, and infrastructure-as-code in a cloud-native environment.
  • Work with the data science team on their ML pipelines, giving data scientists the infrastructure and automation they need to deploy models to production with speed and confidence.
  • Collaborate with cross-functional teams to embed GenAI agents into business processes, creating smart workflows that boost efficiency and reduce manual work.
  • Develop frameworks and internal tooling that empower other teams to safely adopt AI and accelerate innovation.
  • Optimize data infrastructure for performance and cost-efficiency, with a focus on BigQuery optimization.
  • Ensure high data quality and integrity across large-scale ETL processes. Work closely with analysts, data scientists, and product managers to support data modeling, governance, and analytical initiatives.

Requirements:

  • 5+ years of experience as a Data Engineer.
  • Strong programming skills in Python and SQL, with a focus on clean, maintainable, production-grade code.
  • Proven experience building data pipelines with Airflow.
  • Hands-on experience with modern analytical databases
  • Experience working with cloud platforms.
  • Solid knowledge of data modeling, database design, and performance optimization.
  • Strong problem-solving abilities, analytical mindset, and attention to detail.
  • Experience working in production-grade environments.
  • Excellent communication and collaboration skills.
  • Familiarity with modern CI/CD, observability, and infrastructure-as-code practices.
  • Experience with Kubernetes, Docker, and Terraform.

Nice to have:

  • Experience implementing ML and GenAI capabilities in data workflows.
  • Familiarity with AI coding assistants (e.g., Cursor, Claude Code, Copilot) to accelerate development.

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.

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