Data Engineer
Domes Resorts & Reserves
| Company | Domes Resorts & Reserves |
| Category | Engineering |
| Location | Athens |
| Remote | On-site (inferred) |
| Employment | Full-time |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 1 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (workable) |
Description
“Working with Domes is like being part of a family, it’s like coming home.” Are you ready to become member of one of the fastest paced hospitality Group? Do you want to be part of a growing E-Commerce, Intelligence & Innovation team? At the Domes Resorts, as we expand with new Resort openings on an almost annual basis, our main goal is to create a unique environment for both our guests and our people. By joining the Domes corporate & regional teams, you instantly play a vital role in our development, by assuming a position that will set you apart from the competition and allow you to develop meaningful relationships and grow personally and professionally, in a safe, strong, and sustainable environment. Are you passionate about Data Engineering, or looking for a new challenge in the hospitality industry? Join our dynamic team at Domes Resorts and play a key role in supporting our team to drive business growth. This multifaceted role seeks a highly organized and results-driven Data Engineer to join our E-Commerce, Intelligence & Innovation team. The successful candidate will be responsible for designing, building, and maintaining scalable data pipelines and integrations that support business intelligence, reporting, and decision-making across the organization. The role plays a key part in connecting and integrating data from multiple systems, including hotel Property Management Systems (PMS), ensuring data accuracy, availability, and consistency across all platforms. Working closely with cross-functional teams, the ideal candidate will contribute to the development of a robust data infrastructure that supports the company’s commercial and operational objectives. Data Engineer Some of the responsibilities you will be entrusted with: Design, develop, and maintain scalable and reliable data pipelines to support business intelligence, reporting, and analytics needs. Build and optimize ETL/ELT processes to ensure efficient data extraction, transformation, and loading across multiple systems. Develop and maintain robust data architecture that ensures high performance, scalability, and data availability. Integrate and manage data connections with hotel Property Management Systems (PMS) and various third-party platforms via APIs and other data ingestion methods. Ensure seamless data synchronization between internal and external systems, maintaining consistency and reliability. Monitor and maintain integrations, proactively identifying and resolving issues to minimize downtime. Implement data quality checks, validation rules, and monitoring systems to ensure accuracy and integrity of data across all platforms. Troubleshoot and resolve data pipeline issues, ensuring timely recovery and minimal disruption to business operations. Establish and maintain data governance practices, including documentation, standards, and best practices. Collaborate closely with cross-functional teams (e.g., commercial, operations, finance) to understand data requirements and deliver tailored data solutions. Support reporting and analytics initiatives by providing clean, structured, and accessible datasets. Contribute to continuous improvement of data processes, tools, and infrastructure to enhance efficiency and scalability. Document data flows, systems, and processes to ensure transparency and maintainability. Stay up to date with emerging data engineering tools, technologies, and best practices, recommending improvements where appropriate. Requirements Useful to have: Bachelor’s degree in Computer Science, Data Engineering, or a related field. 1–2+ years of experience in data engineering or similar roles. Experience with SQL, data modeling, and relational databases (e.g., PostgreSQL, MySQL). Proficiency in Python or a similar programming language. Experience integrating data from multiple sources, including APIs. Familiarity with data pipeline tools (e.g., Microsoft Fabric, Azure
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