Sr. Engineer - IT Data Analytics

Wynn Resorts seeks to create a system of data, analysis and actions to better attract guests and scale the highly personalized services and experiences that top guests know Wynn resorts for, thereby driving greater loyalty and frequency while also selling more services through ever-increasing levels of personalization.  The Data Engineer will create and manage solutions which turn data into knowledge.Roles and responsibilities for the Senior Data Engineer are:Participate in Architecture Development and Solution Design: Engage in sessions to develop and design data architecture solutions that align with business needs.Driving Data Quality Processes: Implement data profiling, data cleansing, and other processes to ensure high data quality.Guide and Mentor: Provide guidance and mentorship to other data engineers within the team.Design and Implement Data Ingestion Patterns: Define, design, and implement various data ingestion patterns using modern technologies such as Databricks, Airflow, Kafka and SnowflakeLead Data Modeling Workstream: Develop data models that meet business requirements using tools like Erwin.Participate in Data Governance Initiatives: Contribute to data governance efforts to ensure compliance and data integrity.Ensure Data Integrity and Quality: Maintain data integrity and quality throughout the data flow and develop solutions to uphold these standards.Document Data Flows and Design Specifications: Create comprehensive documentation for data flows and design specifications.Evaluate Data Tools: Assess and recommend the best-fit data ingestion, integration, and replication tools for cloud-based data analytics use cases.Implement Real-Time Data Transfers: Ensure that data is available to the business in real-time, at the right time and place.Maintain and Support Data Ingestion Tools: Oversee the maintenance and support of data ingestion tools and solutions.Leverage Advanced Technologies: Utilize advanced technologies such as Large Language Models (LLMs), Predictive Machine Learning (ML), Robotic Process Automation (RPA), and AI Agents to enhance data processes and analytics