Do not wait to apply after reading this description a high application volume is expected for this opportunity. Key Responsibilities Define and lead the architecture and design of enterprise data platforms using Snowflake on AWS. Architect scalable data ingestion frameworks for integrating multiple source systems into the cloud data platform. Design and govern data transformation frameworks using DBT. Define and enforce data modelling standards including dimensional modelling, star schema, and enterprise data models. Lead architecture reviews and solution design discussions for new data initiatives. Optimize Snowflake performance, workload management, and cost governance. Establish data governance frameworks including access control, data security, and compliance standards. Design and support AI/ML-ready data architecture for advanced analytics and predictive modelling. Provide architectural guidance to data engineering, BI, and analytics teams. Design architecture to support data consumption for reporting systems, operational applications, and analytics platforms. Implement automation, orchestration, and scalable pipeline frameworks using tools such as Apache Airflow. Collaborate with business stakeholders and technical teams to align the data platform with enterprise data strategy. Support hospitality analytics use cases, including guest behaviour analysis, booking trends, revenue analytics, and operational reporting. Required Technical Skills Data Platform Strong expertise in Snowflake Deep knowledge of Snowflake architecture, performance tuning, data sharing, security, and workload optimization. Cloud Platform Strong experience with Amazon Web Services, including: S3 IAM AWS Glue Lambda CloudWatch Data Transformation Strong experience with DBT for enterprise-scale data modelling, testing, and transformation pipelines. Programming / Query Strong expertise in SQL for data transformation and performance optimization Python (preferred) for automation and data engineering tasks. Data Engineering Enterprise ETL / ELT pipeline architecture Data warehousing and enterprise data modelling Dimensional modelling (Star Schema, Snowflake Schema) Data pipeline scalability and reliability design. AI / Data Science Exposure Experience supporting AI/ML data pipelines and data preparation for machine learning models. Understanding of predictive analytics, recommendation engines, and customer behaviour analytics. Ability to design AI-ready data platforms for future analytics use cases. Preferred Skills Experience with Apache Airflow for pipeline orchestration. Knowledge of CI/CD pipelines, DevOps, and Git-based development workflows. Experience with data governance, metadata management, and enterprise data catalog tools. xehkeey Experience with BI tools such as Tableau Microsoft Power BI. Domain experience in hospitality, travel, or hotel systems, including reservation systems, guest analytics, and operational reporting.