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Open nowPosted 29 hours ago

Sr. Engineer - IT Data Analytics

Wynn Resorts138 open roles

Where
Las Vegas, NV, United States
Work mode
On site
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Your applicationOpen nowSr. Engineer - IT Data AnalyticsWynn Resorts · Las Vegas, NV, United States

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The clock on this job

Early applications get read.

11.9% of postings close within 7 days. Measured by our own scanner across the market. Wynn Resorts postings stay open a median of 33 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 29 hours ago

Wynn Resorts median: 33 days open

The posting

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

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.

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