Sr. Engineer - IT Data Analytics

Wynn Resorts, Limited; Las Vegas (NV); On-site; USD 130,000 - 190,000; Full time

Job summary

Wynn Resorts Limited is building an integrated data, analytics, and action system to attract guests and scale highly personalized service. The Senior Data Engineer on the CIP team designs, builds, and operates cloud data pipelines and models turning guest, gaming, and hospitality data into real-time knowledge for the business.

Key responsibilities include implementing production schemas in Snowflake and Databricks, enabling real-time data delivery, and integrating PMS, player tracking, CRM, and

Qualifications

• Six or more years in data engineering with end-to-end cloud analytics projects.
• Experience building pipelines on Microsoft Azure, Snowflake, and Databricks.
• Advanced SQL with large datasets; complex transformations and tuning.
• Advanced Python for data engineering, including PySpark/Snowpark; automated testing.
• Hands-on data modeling in cloud warehouses or lakehouses; dimensional/medallion.
• CI/CD and Git workflows for data pipelines; Azure DevOps.
• Experience using AI coding assistants in production with secure practices.

Responsibilities

• Contribute engineering input on feasibility, performance, and cost in design sessions.
• Implement physical data models and deploy production schemas in Snowflake and Databricks.
• Evaluate ingestion, integration, replication options with POCs and benchmarking.
• Document data flows, specs, and data contracts for downstream teams.
• Design reusable batch and streaming ingestion using Databricks, Airflow, Kafka, Snowflake.
• Deliver real-time data to business; ensure guest and operational data availability.
• Integrate core hospitality and gaming source systems (PMS, player tracking, CRM).
• Build pipelines as code with CI/CD, automated testing, and environment promotion.
• Maintain ingestion tooling with monitoring, alerting, cost and performance tuning.

Skills

Cloud data engineering

SQL

Python PySpark

Data modeling

CI/CD

AI tooling

Tools

Azure

Snowflake

Databricks

Airflow

Kafka

GitHub Copilot

Job description

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

• 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.
• 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.