Vista is the world’s leading global business aviation company, providing worldwide business flight services through its network of subsidiaries and a team of over 4,000 experts. A global group headquartered in Dubai, Vista integrates a unique portfolio of companies to offer asset-free services that cover all key aspects of business aviation, including guaranteed and on-demand global flight coverage, subscription and membership solutions, and trading and management services.
A career at Vista means stepping into an environment where you’re trusted with real autonomy and responsibility from day one. Whether you're keeping our aircraft airworthy, flying our clients across the globe, or working in one of our corporate teams, you’ll move fast, deliver impact quickly, and grow through hands‑on learning and close collaboration within a supportive global community.
The Enterprise Data Architect is responsible for the data modeling and architecture strategy spanning Vista Global’s Enterprise Data Warehouse (Snowflake) and Operational Data Store (ODS). This role defines how data is structured, integrated, and governed as it moves from operational systems into the ODS and downstream into the warehouse, ensuring the resulting data models are scalable, well-documented, and trusted. The architect serves as the subject-matter expert on data modeling and integration design, partnering closely with data engineering, application, and analytics teams to translate business requirements into robust, reusable data models.
• Design and maintain enterprise data models for the Snowflake data warehouse and Operational Data Store (ODS), ensuring consistency, scalability, and alignment with business needs.
• Own the data architecture strategy connecting operational systems, the ODS, and the enterprise data warehouse, including integration and data flow design between layers.
• Define and document data modeling standards, including naming conventions, modeling patterns (e.g., dimensional modeling, 3NF, data vault), and best practices used across the data organization.
• Partner with data engineers to design and review ELT/ETL pipelines (dbt, Airflow) that move data reliably from source systems through the ODS and into the warehouse.
• Define event payload schemas and data contract standards for new topics on the Kafka data backbone, ensuring clean, well-documented events for downstream ODS and warehouse consumption.
• Drive data governance practices, including metadata management, data lineage, data quality standards, and documentation, using tools such as Open Metadata.
• Evaluate new data sources, systems, and integration requirements, and design the corresponding data models and ingestion patterns.
• Serve as the subject-matter expert on data modeling and architecture, providing design reviews and technical guidance to data engineers, analysts, and application teams.
• Partner with product, analytics, and application teams to translate business requirements into well-structured, reusable data models that support enterprise reporting and analytics needs.
• Supervisory Responsibilities: None. This is an individual-contributor position with no direct reports.
• Bachelor’s degree in Computer Science, Engineering or related discipline required
• Minimum 8 years of total professional experience in data engineering, database development, or related fields.
• At least 3 years of experience specifically in a data architecture or senior data modeling role.
• Hands-on experience designing and modeling data for both a cloud data warehouse (Snowflake preferred) and a relational operational data store (PostgreSQL/Aurora preferred) is required.
• Experience defining event payload schemas and data contracts on a streaming/messaging platform such as Kafka is required.
• Aviation industry experience preferred.
• Deep proficiency in SQL, data modeling techniques (dimensional modeling, 3NF, data vault), and ELT/ETL design principles.
• Experience with orchestration tools such as Airflow.
• Working knowledge of PostgreSQL/Aurora and cloud data warehouse platforms (Snowflake preferred), including performance and schema design considerations for both transactional and analytical workloads.
• Ability to define and enforce data architecture standards, modeling best practices, and documentation across warehouse and ODS environments.
• Knowledge of Master Data Management (MDM) principles and metadata management frameworks.
• Strong stakeholder management skills and the ability to partner effectively across technical and non-technical teams.
• Excellent communication skills with the ability to articulate technical concepts to diverse audiences.
• Detail-oriented with a strong commitment to data quality, consistency, and governance across systems.