Data Warehouse Engineer
Mohegan Sun, Montville, CT, United States
Position Summary
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.
Primary Duties and Responsibilities
ETL Development and Data Integration: The Data Warehouse Engineer will be responsible for designing, developing, and maintaining complex ETL workflows using enterprise‑class tools such as Informatica. This includes extracting data from multiple source systems, applying business transformation logic, and loading data into target data warehouse environments. The role requires implementing automated validation procedures to ensure data accuracy and integrity across all warehouse feeds, as well as developing Python scripts and APIs for data integration, automation, and custom data processing tasks.
Data Warehouse Design and Optimization: A core responsibility of this role is to design and maintain efficient data warehouse structures, schemas, tables, views, and materialized views that support business intelligence requirements. The Data Warehouse Engineer will be responsible for performance planning, tuning, and optimization including warehouse sizing, query optimization, clustering keys, and data partitioning strategies. This includes 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.
Technical Documentation and Data Governance: The Data Warehouse Engineer will create and maintain comprehensive technical documentation including data catalogs, structural diagrams, ETL process flows, and data lineage documentation. This includes documenting data definitions, business rules, transformation logic, and end‑user warehouse assets to ensure transparency and support data governance initiatives across the organization.
Business Intelligence Support and Collaboration: Provide Level III technical support for business intelligence and decision support tools, working directly with business users to troubleshoot complex data issues. Collaborate with business stakeholders and management to understand analytical requirements and translate them into technical specifications. Develop reports and data visualizations using enterprise reporting tools, ensuring that data assets are meaningful, efficient, and accurate for end‑user consumption.
Data Pipeline Development and API Integration: Design and implement modern data pipelines that integrate with various systems through APIs and web services. Develop Python‑based solutions for data extraction, transformation, and automation tasks. Leverage data warehouse’s native capabilities for continuous data ingestion, streams and tasks for data pipeline orchestration, and external functions for API integration. Work with other teams to ensure seamless integration of new data sources and maintain the reliability of existing data flows in a 7x24x365 enterprise environment.
Project Execution and Continuous Improvement: Execute approved work requests based on business priorities, working on project teams to create or modify existing data reports and warehouse assets. Stay current with emerging technologies, tools, and methodologies in data warehousing and data engineering, particularly Snowflake and Informatica platform enhancements and best practices. Evaluate and recommend new approaches for improving data infrastructure, ETL processes, and overall data warehouse capabilities.
Perform additional duties and responsibilities as assigned.
Promote and uphold Mohegan’s core values and purpose through daily actions and decision‑making.
Deliver and support a high standard of customer service.
Provide support for applications operating in a 24/7/365 enterprise environment.
Maintain accurate reporting in accordance with Mohegan Information Systems policies.
Minimum Education And Qualifications
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.
Competencies
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.
Training Requirements
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.
Physical Demands And Work Environment
Office work environment / 3 days in office.
Must be able to sit in front of a computer screen for extended periods of time.
Ability to work a flexible schedule, including occasional evenings and weekends.
On‑call availability with a company‑issued cell phone.
Willingness to travel occasionally (up to 10%).
Work Shift
Regular
Mohegan Sun practices Native American Preference in hiring. "Native American" means an individual who is a duly enrolled member of the Mohegan Tribe or any group of Native Americans recognized by the Mohegan Tribe, The United States of America, or the State of Connecticut.
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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.
Primary Duties and Responsibilities
ETL Development and Data Integration: The Data Warehouse Engineer will be responsible for designing, developing, and maintaining complex ETL workflows using enterprise‑class tools such as Informatica. This includes extracting data from multiple source systems, applying business transformation logic, and loading data into target data warehouse environments. The role requires implementing automated validation procedures to ensure data accuracy and integrity across all warehouse feeds, as well as developing Python scripts and APIs for data integration, automation, and custom data processing tasks.
Data Warehouse Design and Optimization: A core responsibility of this role is to design and maintain efficient data warehouse structures, schemas, tables, views, and materialized views that support business intelligence requirements. The Data Warehouse Engineer will be responsible for performance planning, tuning, and optimization including warehouse sizing, query optimization, clustering keys, and data partitioning strategies. This includes 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.
Technical Documentation and Data Governance: The Data Warehouse Engineer will create and maintain comprehensive technical documentation including data catalogs, structural diagrams, ETL process flows, and data lineage documentation. This includes documenting data definitions, business rules, transformation logic, and end‑user warehouse assets to ensure transparency and support data governance initiatives across the organization.
Business Intelligence Support and Collaboration: Provide Level III technical support for business intelligence and decision support tools, working directly with business users to troubleshoot complex data issues. Collaborate with business stakeholders and management to understand analytical requirements and translate them into technical specifications. Develop reports and data visualizations using enterprise reporting tools, ensuring that data assets are meaningful, efficient, and accurate for end‑user consumption.
Data Pipeline Development and API Integration: Design and implement modern data pipelines that integrate with various systems through APIs and web services. Develop Python‑based solutions for data extraction, transformation, and automation tasks. Leverage data warehouse’s native capabilities for continuous data ingestion, streams and tasks for data pipeline orchestration, and external functions for API integration. Work with other teams to ensure seamless integration of new data sources and maintain the reliability of existing data flows in a 7x24x365 enterprise environment.
Project Execution and Continuous Improvement: Execute approved work requests based on business priorities, working on project teams to create or modify existing data reports and warehouse assets. Stay current with emerging technologies, tools, and methodologies in data warehousing and data engineering, particularly Snowflake and Informatica platform enhancements and best practices. Evaluate and recommend new approaches for improving data infrastructure, ETL processes, and overall data warehouse capabilities.
Perform additional duties and responsibilities as assigned.
Promote and uphold Mohegan’s core values and purpose through daily actions and decision‑making.
Deliver and support a high standard of customer service.
Provide support for applications operating in a 24/7/365 enterprise environment.
Maintain accurate reporting in accordance with Mohegan Information Systems policies.
Minimum Education And Qualifications
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.
Competencies
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.
Training Requirements
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.
Physical Demands And Work Environment
Office work environment / 3 days in office.
Must be able to sit in front of a computer screen for extended periods of time.
Ability to work a flexible schedule, including occasional evenings and weekends.
On‑call availability with a company‑issued cell phone.
Willingness to travel occasionally (up to 10%).
Work Shift
Regular
Mohegan Sun practices Native American Preference in hiring. "Native American" means an individual who is a duly enrolled member of the Mohegan Tribe or any group of Native Americans recognized by the Mohegan Tribe, The United States of America, or the State of Connecticut.
#J-18808-Ljbffr