Smarxion · 4 hours ago
Data Architect
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Cloud Data ServicesConsulting
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Responsibilities
Analyze and document data from various casino systems, including slots, table games, F&B, hotel management systems, and online platforms.
Design a scalable and flexible data architecture to support the casino analytics platform, enabling real-time data processing and advanced analytics.
Integrate on-premise and cloud-based casino data sources, ensuring smooth data flow between gaming, hotel, F&B, and online systems.
Develop efficient ETL/ELT processes to extract, transform, and load data into the platform, ensuring high data quality and performance.
Design data models for structured and unstructured data, optimizing for scalability, flexibility, and future enhancements.
Implement data governance and security practices to ensure the integrity, accuracy, and regulatory compliance of the data.
Architect real-time data streaming and processing capabilities to enable dynamic insights into gaming floor activity and player behaviors.
Work closely with data engineers, data scientists, and business analysts to understand data requirements and translate them into a scalable architecture.
Enable advanced analytics, machine learning, and predictive modeling capabilities by ensuring clean, accessible data across the platform.
Ensure the data architecture supports fast query performance, real-time analytics, and is capable of scaling as the platform grows.
Qualification
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Required
Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
7+ years of experience in data architecture, data engineering, or a similar role.
Extensive experience working with casino management systems, F&B systems, hotel management systems, and online gaming platforms.
Proven track record of architecting and delivering data platforms at scale in data-heavy industries.
Deep knowledge of relational databases (e.g., SQL Server, MySQL, Oracle) and NoSQL databases (e.g., MongoDB, Cassandra).
Strong expertise in cloud platforms (Azure, AWS, or Google Cloud)
Experience with real-time data streaming platforms (e.g., Kafka, Spark) and building low-latency pipelines.
Expertise in API integrations and data exchange between various systems.
Proficiency with ETL/ELT tools and scripting languages (e.g., Python, .Net Core, SQL).
Strong background in data modeling, including star/snowflake schemas, for analytics and reporting.
Experience with BI tools such as Power BI, Tableau, or similar.
Excellent communication and stakeholder management skills to collaborate with technical and non-technical teams.
Strong analytical and problem-solving abilities, with a focus on delivering solutions that meet business objectives.