Sr. Engineer - Data Analytics

Wynn Resorts•Las Vegas, NV

3h•Onsite

About The Position

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.

Requirements

Holds a BSc / BA in computer science, engineering or similar disciplines
Proven experience in designing cloud-based data architecture
Able to design end-to-end solutions for data ingestion and data management
Proven experience as a data engineer in a cloud-based data analytics project; at least 3 similar project experience
Strong knowledge of Snowflake, Databricks, Airflow, Kafka & Azure Data Platform
Hands-on experience in cloud-based data ingestion tools
Understanding & the ability to evaluate new age & best fit tools that may be new in the market
Expertise in cloud-based data ingestion (Microsoft Azure)
Strong knowledge & experience in cloud-based data warehousing & analytics
Strong understanding of data models; hands-on experience in developing large scale complex data models that are fit for cloud data warehouses using Erwin
Familiarity with BI and analytics
Expert level experience with programming languages like SQL, Python, Spark etc.
Proven abilities to take initiative and be innovative
Analytical mind with a problem-solving aptitude
Experience in the casino resorts industry
This position is required to be in-office at our Las Vegas, Nevada property
A passion for demonstrating the art of the possible in terms of how data and technology enable world-class customer experiences and drive customer loyalty
Track record of success influencing without direct authority and balancing between competing priorities while remaining flexible and creative
Strong ability to build and strengthen team engagement and align resources to strategy, key tactics and measures; proven ability to establish clear aligned goals and objectives with a timely feedback loop
Outstanding written and verbal communication skills with the ability to work up, down and across organizational levels. The ideal candidate will have a direct, but tactful communication style
Strong business acumen and problem-solving skills, along with the ability to assess current practices, identify opportunities for improvement, build consensus and drive the implementation of related changes

Responsibilities

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 Snowflake
Lead 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