Analyst - IT Data Analytics

Job Description

The Data Analyst, Wynn's Customer Data Platform (CDP) plays a central role in translating raw data into actionable guest and player intelligence across Wynn Resorts' North American properties. This role sits at the intersection of CDP analytics and marketing technology — contributing to data quality governance, enterprise data modeling, and analytical support for Wynn's martech and CRM platforms. Work product directly influences campaign execution, guest engagement strategy, and business decisions across WLV and EBH.

The ideal candidate combines advanced SQL and analytical skills with hands-on experience in martech data flows, CDP/CRM ecosystems, and data quality frameworks. They understand how marketing data moves — from source system through integration layer into the data warehouse and back into activation — and can translate that understanding into defensible analysis and measurable quality standards.

Key Responsibilities

CDP Analytics & Marketing Intelligence

• Develop and maintain analytical models, dashboards, and reports in support of CRM, player development, and marketing operations across WLV and EBH.
• Query enterprise data warehouse sources to answer ad hoc business questions and support recurring reporting cadences — including guest segment performance, campaign response analysis, channel attribution, and martech platform utilization.
• Measure and report on end-to-end campaign and channel performance; surface lift, conversion, and engagement insights to the martech team and business stakeholders.
• Support audience validation workflows to ensure marketing segment definitions and contact data align with enterprise data warehouse source-of-truth records.
• Partner with the Lead Data Architect and senior team members to translate business requirements into well-structured SQL queries and analysis workflows; document methodology and assumptions for every deliverable.
• Identify trends, anomalies, and behavioral patterns in guest engagement, transactional, and survey data; present findings in clear, executive-ready formats.
• Support high-visibility analytics workstreams across the CDP and martech portfolio as a hands-on analytical contributor.

Data Quality Measurement & Governance

• Design, implement, and maintain data quality rules across CDP and martech source systems — covering CRM, marketing automation, guest feedback, and enterprise integration data feeds landing in the data warehouse.
• Define measurable DQ dimensions (completeness, accuracy, consistency, timeliness, uniqueness) with quantifiable thresholds for each critical martech and CDP data domain; instrument rule violations as first-class delivery backlog items.
• Build and maintain automated DQ monitoring pipelines; generate DQ scorecards and escalation alerts for the CDP team, martech operators, and downstream analytics consumers.
• Own data quality for martech activation data — validate contact eligibility, suppression accuracy, and segment membership against enterprise data warehouse records prior to campaign execution.
• Conduct root cause analysis on data quality failures across martech and CRM data feeds; coordinate with data engineering on remediation and upstream fix prioritization.
• Maintain a living data quality rule catalog aligned to the CDP data dictionary and team delivery backlog; propose and shepherd rules through the sprint-planning process.
• Contribute DQ rules and validation logic supporting guest identity resolution — including match confidence, deduplication, and profile completeness standards across properties.

Data Modeling Participation

• Participate actively in dimensional and relational data modeling sessions for CDP subject areas — including guest profiles, gaming activity, hospitality transactions, martech engagement history, and guest feedback data.
• Contribute to logical and physical data model design in the enterprise data warehouse using star and snowflake schema patterns; document grain, keys, measures, and slowly changing dimension (SCD) strategies for CDP and martech domains.
• Apply disciplined SQL practices to all schema changes: read before write, single-purpose changes, reversibility, and documented rollback steps for all DDL/DML modifications.
• Collaborate with data engineers on martech and CRM integration schemas — ensuring source system data from marketing automation, customer feedback, and CRM platforms is correctly modeled for analytical consumption.
• Review data models for alignment with CDP analytics and martech activation needs; surface gaps between source system structures and analytical consumption requirements during sprint planning.

Martech Partnership & Cross-Functional Delivery

• Serve as the primary analytical partner for the martech team — supporting data validation, campaign performance measurement, audience QA, and analytical requests across Wynn's marketing technology platforms.
• Partner with the martech team on guest feedback and survey data integrations — validating ingestion pipelines, supporting sentiment and voice-of-guest reporting, and ensuring data quality upstream of analytical consumption.
• Work within the CDP team's delivery framework — writing or contributing to User Stories, Acceptance Criteria, and sprint tasks aligned to the team's ADO backlog structure.
• Coordinate with integration and CRM teams to validate data payloads flowing into the enterprise data warehouse; flag data discrepancies and latency issues to the data engineering team for remediation.
• Participate in enterprise BI governance — maintaining data source certifications, monitoring reporting pipeline performance, and ensuring published views adhere to CDP data standards.

Qualifications

Required

• At least three (3) years of experience in a data analyst or marketing analytics role, preferably within a martech, CRM, loyalty, or consumer-facing industry context
• Advanced SQL proficiency — window functions, CTEs, complex joins, performance optimization; Snowflake experience strongly preferred
• Hands-on experience with at least one enterprise martech, CRM, or guest feedback platform as an analytical consumer — marketing automation, customer engagement, or voice-of-guest tooling.
• Demonstrated experience designing and implementing data quality rules and monitoring frameworks in a production data warehouse environment
• Working knowledge of dimensional modeling concepts (star schema, SCD Types 1/2/3, grain definition, surrogate keys) in the context of marketing and CRM data domains
• Proficiency with Tableau Desktop and Tableau Cloud — including calculated fields, LOD expressions, data blending, and published data source management
• Experience working with structured data from CRM, marketing automation, or transactional systems; ability to interpret XML/JSON payloads and map to target schemas
• Strong analytical communication skills — ability to frame findings using structured narratives (situation/complication/resolution) for VP/Director audiences
• Comfort with Agile/Scrum delivery — writing user stories, estimating effort, and working within sprint-planning frameworks

Preferred

• Deeper platform experience across enterprise martech or CRM tools — marketing automation, digital engagement platforms, customer feedback systems, or loyalty and CRM analytics
• Familiarity with hospitality or gaming data domains — patron/placer profiles, hotel operations, CRM and loyalty program data, or reinvestment analytics
• Experience building or validating CDP audience segments and understanding segment membership logic (inclusion/exclusion rules, recency/frequency/monetary criteria)
• Experience with Databricks (PySpark or SQL notebooks) or similar distributed compute platforms for large-scale data quality or martech pipeline work
• Experience with Azure cloud services (Azure Data Factory, Azure Blob Storage, Azure AI Foundry) in a marketing data or analytics engineering context
• Familiarity with data catalog tools (Microsoft Purview, Atlan, or equivalent) and data lineage documentation for martech and CDP data domains
• Proficiency with Python for data wrangling, pipeline scripting, or analytical automation (pandas, SQLAlchemy, requests)

Additional Information

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