Data Warehouse Engineer

Mohegan Sun•Montville, CT

1d•Hybrid

About The Position

The Data Warehouse Engineer is responsible for designing, developing, and maintaining enterprise data warehouse infrastructure and ETL (Extract Transform Load) solutions that support strategic decision-making and operational efficiency. This role requires expertise in data integration, database management, and modern data engineering. The position will work closely with business stakeholders and cross-functional teams to understand requirements, implement scalable data solutions, and ensure the availability of high-quality data assets for business intelligence and analytics initiatives.

Requirements

Bachelor’s degree in computer science, Computer Applications, Engineering, Business, or a related field.
Five years of proven experience in data warehousing, ETL development, and database management for a large organization.
Demonstrated expertise with ETL tools (e.g., Informatica) and business intelligence platforms such as Snowflake, Power BI, and Cognos.
Proficiency in SQL and cloud‑based data warehouse technologies.
Hands‑on experience with the Snowflake data platform, including architecture design, administration, and performance optimization.
Experience using Python for data integration, automation, or related data engineering tasks.
Knowledge of API development and system integration.
Strong written and verbal communication skills.
Demonstrated analytical and critical thinking abilities.
Proven ability to work collaboratively, with strong self‑awareness and interpersonal skills.
Obtains and maintains at least one or more applicable gaming licenses in multiple jurisdictions.
Advanced proficiency in SQL and relational database management systems.
Advanced expertise in Snowflake data platforms, including SnowSQL, Snowpipe, Streams, Tasks, and data sharing.
Strong competency in API development, system integration, and web services.
Working knowledge of governance and service management frameworks, including COBIT and ITIL.
Strong understanding of the software development lifecycle (SDLC) and data engineering best practices.
Proficiency in data modeling concepts and data architecture methodologies.
Mohegan corporate and department policies and procedures.
Appropriate regulations that pertain to Mohegan information systems.
Purchase request review and approval with enterprise supply-chain management application.
Review and analysis of department timesheet information.
Mohegan budget planning and analysis process and procedures.

Responsibilities

Designing, developing, and maintaining complex ETL workflows using enterprise-class tools such as Informatica.
Extracting data from multiple source systems, applying business transformation logic, and loading data into target data warehouse environments.
Implementing automated validation procedures to ensure data accuracy and integrity across all warehouse feeds.
Developing Python scripts and APIs for data integration, automation, and custom data processing tasks.
Designing and maintaining efficient data warehouse structures, schemas, tables, views, and materialized views that support business intelligence requirements.
Performance planning, tuning, and optimization including warehouse sizing, query optimization, clustering keys, and data partitioning strategies.
Implementing best practices for data modeling, leveraging features such as time travel, zero-copy cloning, and data sharing capabilities to ensure query efficiency and system scalability.
Creating and maintaining comprehensive technical documentation including data catalogs, structural diagrams, ETL process flows, and data lineage documentation.
Documenting data definitions, business rules, transformation logic, and end-user warehouse assets to ensure transparency and support data governance initiatives across the organization.
Providing Level III technical support for business intelligence and decision support tools, working directly with business users to troubleshoot complex data issues.
Collaborating with business stakeholders and management to understand analytical requirements and translate them into technical specifications.
Developing reports and data visualizations using enterprise reporting tools, ensuring that data assets are meaningful, efficient, and accurate for end-user consumption.
Designing and implementing modern data pipelines that integrate with various systems through APIs and web services.
Developing Python-based solutions for data extraction, transformation, and automation tasks.
Leveraging data warehouse’s native capabilities for continuous data ingestion, streams and tasks for data pipeline orchestration, and external functions for API integration.
Working with other teams to ensure seamless integration of new data sources and maintain the reliability of existing data flows in a 7x24x365 enterprise environment.
Executing approved work requests based on business priorities, working on project teams to create or modify existing data reports and warehouse assets.
Staying current with emerging technologies, tools, and methodologies in data warehousing and data engineering, particularly Snowflake and Informatica platform enhancements and best practices.
Evaluating and recommending new approaches for improving data infrastructure, ETL processes, and overall data warehouse capabilities.
Performing additional duties and responsibilities as assigned.
Promoting and upholding Mohegan’s core values and purpose through daily actions and decision‑making.
Delivering and supporting a high standard of customer service.
Providing support for applications operating in a 24/7/365 enterprise environment.
Maintaining accurate reporting in accordance with Mohegan Information Systems policies.