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 strong expertise in data integration, database management, and modern data engineering practices. The position collaborates closely with business stakeholders and cross-functional teams to gather requirements, implement scalable data solutions, and ensure the availability of high-quality, reliable data assets for business intelligence and analytics initiatives.
Key Responsibilities
ETL Development and Data Integration
- Design, develop, and maintain complex ETL workflows using enterprise tools such as Informatica
- Extract data from diverse source systems, apply transformation logic, and load into data warehouse environments
- Implement automated validation processes to ensure data accuracy and integrity
- Develop Python scripts and APIs for automation, data processing, and integration tasks
Data Warehouse Design and Optimization
- Design and maintain efficient data warehouse structures (schemas, tables, views, materialized views)
- Perform performance tuning, including query optimization, clustering keys, and partitioning strategies
- Apply best practices in data modeling and architecture
- Utilize advanced platform features such as time travel, zero-copy cloning, and data sharing
- Ensure scalability, efficiency, and optimal system performance
Business Intelligence Support and Collaboration
- Provide Level III technical support for BI and decision support tools
- Collaborate with business stakeholders to translate requirements into technical solutions
- Troubleshoot complex data issues
- Develop reports and visualizations using tools such as Power BI and Cognos
- Ensure data accuracy, usability, and efficiency for business users
Data Pipeline Development and API Integration
- Design and implement scalable modern data pipelines
- Develop Python-based solutions for data ingestion and transformation
- Integrate systems through APIs and web services
- Leverage platform capabilities such as:
- Streams and Tasks
- Continuous data ingestion (e.g., Snowpipe)
- External functions for integrations
- Ensure reliability and scalability in a 24/7/365 enterprise environment
Required Skills & Experience
- Bachelor’s degree in Computer Science, Engineering, Business, or related field
- Minimum 5 years of experience in data warehousing, ETL development, and database management
- Strong expertise with Informatica and BI tools such as Snowflake, Power BI, and Cognos
- Advanced proficiency in SQL and cloud-based data warehouse technologies
- Hands-on experience with Snowflake architecture, administration, and optimization
- Experience using Python for data engineering tasks
- Knowledge of API development and system integration
- Strong analytical, problem-solving, and communication skills
- Demonstrated ability to collaborate effectively across teams
- Ability to obtain and maintain required gaming licenses in multiple jurisdictions
Preferred Experience
- Advanced SQL and relational database expertise
- Deep knowledge of Snowflake ecosystem (SnowSQL, Snowpipe, Streams, Tasks, Data Sharing)
- Strong understanding of data modeling and architecture principles
- Experience with API development and integration frameworks
- Knowledge of governance frameworks such as COBIT and ITIL
- Solid understanding of Software Development Lifecycle (SDLC) and data engineering best practices