Sr. Engineer IT Data Analytics

Wynn Resorts is building an integrated system of data analytics and action to attract guests and scale the highly personalized service our top guests know us for driving loyalty visit frequency and revenue through ever-increasing levels of personalization. The Senior Data Engineer is a hands-on senior engineer on the Customer Intelligence Platform (CIP) team responsible for designing building and operating the cloud data pipelines and models that turn guest gaming and hospitality data into trusted real-time knowledge for the business.

Key Responsibilities

Data Architecture & Modeling

• Contribute engineering input on feasibility performance and cost in solution design sessions led by architects across Snowflake Azure Databricks and the Azure data platform.
• Implement physical data models from approved logical designs (dimensional medallion and canonical patterns) and deploy them as production schemas in Snowflake and Databricks.
• Support evaluation of ingestion integration replication and open table format (Delta Lake Apache Iceberg Snowflake Horizon Catalogs) options through hands-on proofs of concept and benchmarking.
• Document implemented data flows technical specifications and data contracts that downstream teams can build against.

Data Ingestion & Pipeline Engineering

• Define design and implement reusable batch and streaming ingestion patterns using Databricks Airflow Kafka and Snowflake.
• Deliver real-time and near-real-time data to the business so guest and operational data is available at the right time and place.
• Integrate core hospitality and gaming source systems including property management player tracking CRM and marketing platforms.
• Build pipelines as code with CI/CD automated testing and environment promotion across development test staging and production.
• Maintain and support ingestion tooling in production owning monitoring alerting incident response and cost and performance tuning.

Data Quality Governance & Security

• Implement data quality controls defined by governance standards including profiling cleansing validation rules and automated checks embedded in every pipeline.
• Build lineage reconciliation and observability into pipelines to maintain data integrity from source to consumption.
• Implement governance standards in the platform including catalog registration access control and classification (e.g. Databricks Unity Catalog Snowflake RBAC).
• Implement PII protection controls including masking least-privilege access and audit logging to meet privacy and gaming regulatory requirements.

AI-Enabled Engineering & Innovation

• Build the data foundations for predictive ML Large Language Models (LLMs) and AI agent use cases including feature pipelines and retrieval-ready datasets.
• Apply automation including RPA and AI agents to streamline data operations and analytics delivery.
• Use AI-assisted development tools (e.g. GitHub Copilot Claude Code) to accelerate pipeline development testing and documentation while maintaining code quality security and review standards.

Technical Leadership & Mentorship

• Guide and mentor data engineers through code reviews pairing and design feedback.
• Set and champion engineering standards reusable frameworks and best practices across the team.
• Translate business requirements from Marketing Gaming Hotel and Analytics stakeholders into technical designs and delivery plans.

Qualifications :

Required

• At least six (6) years of data engineering experience including at least 3 cloud data analytics projects delivered end to end
• Production experience building and operating data pipelines on Microsoft Azure Snowflake and Databricks
• Advanced SQL: complex transformations window functions and performance tuning on large datasets
• Advanced Python for data engineering including PySpark & Snowpark automated testing and reusable packaged code
• Hands-on experience implementing data models (dimensional and medallion) in a cloud warehouse or lakehouse
• CI/CD and Git-based workflows for data pipelines (e.g. Azure DevOps)
• Regular hands-on use of AI coding assistants in production engineering work with sound practices for reviewing testing and securing AI-generated code

Preferred

• Experience in the casino resort hospitality or luxury industries including guest identity resolution or customer data unification
• Orchestration and streaming experience with Airflow and Kafka
• Erwin or comparable modeling tools plus infrastructure as code (Terraform)
• Governance tooling such as Databricks Unity Catalog or Microsoft Purview
• MLOps feature stores vector search or LLM and AI agent data pipelines
• Certifications in Snowflake Databricks or Microsoft Azure

Additional Information :

All your information will be kept confidential according to EEO guidelines.

Remote Work :

No

Employment Type :

Full-time