Data Architect

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Hotel Investor Apps (HIA) is a leading and award-winning cloud-based ERP software provider revolutionizing back-office operations for the hospitality industry. Recognized for its innovative, integrated platform connecting accounting, operations, and business intelligence, HIA empowers hotel management and ownership groups to streamline processes, enhance efficiency, and drive profitability. Join a forward-thinking company dedicated to client success and technological advancement, where you'll contribute to cutting-edge solutions in a collaborative and growth-oriented environment, making a real impact on the future of hotel management.

Job Summary

HIA is seeking a Data Architect to lead the design and implementation of our modern data platform. This individual will define and maintain scalable data platform architectures, and enforce robust data governance practices. The ideal candidate will also have strong secondary skills in Data Engineering to support implementation and workflow development.

Responsibilities

• Define and design the blueprint of HIA’s Data Platform
• Collaborate with the Data Platform Engineers to define, design, and document HIA Data Platform
• Evaluate emerging data technologies, tools, and platforms (e.g., cloud services, databases, BI and analytics tools) to ensure the architecture stays modern and effective
• Make recommendations for adopting new tools and frameworks, ensuring they fit into the overall data strategy
• Design data integration strategies to pull data from various sources (e.g., APIs, databases, cloud platforms) into centralized repositories (e.g., data lakes, warehouses)
• Develop data models (conceptual, logical, and physical) to represent the organization's data assets and how they are structured
• Collaborate with Data Engineers to develop ETL processes that ensure data consistency, quality, and timeliness
• Integrate data from various internal and external data sources (e.g., APIs, on-prem databases, SaaS platforms) into the organization's central data repository
• Implement data validation, cleansing, and transformation steps to ensure high-quality data throughout the pipeline
• Monitor and troubleshoot data pipelines to ensure data quality and reliability

Minimum Qualifications

Preferred Qualifications

Terms

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