What are the responsibilities and job description for the Snowflake Data Engineer position at EA Team, Inc.?
Job Details
We are seeking a highly skilled Snowflake Data Engineer to join our team in Westlake, TX.
This individual will play a crucial role in designing, implementing, and maintaining data solutions that leverage Snowflake and other cloud technologies.
The ideal candidate will have strong experience with Snowflake, Power BI, PL/SQL, Informatica, and cloud platforms (AWS, Azure, Google Cloud Platform).
The Snowflake Data Engineer will be responsible for building and optimizing data pipelines, ensuring data quality, and enabling efficient data reporting and analytics.
Key Responsibilities: Data Architecture and Design:
- Design and implement Snowflake data warehouse solutions tailored to business requirements.
- Build, maintain, and optimize scalable data pipelines using Snowflake and cloud technologies (AWS, Azure, Google Cloud Platform).
- Collaborate with cross-functional teams to gather and understand business requirements for data models and data solutions.
ETL Development and Data Integration:
- Design and develop ETL/ELT processes using Informatica, Snowflake, and PL/SQL.
- Integrate diverse data sources into Snowflake data warehouse and ensure smooth data flow across systems.
- Work on data migration and data transformation projects, ensuring the integration of on-premise and cloud-based data sources.
Performance Optimization:
- Optimize data warehouse performance for query optimization, storage management, and cost reduction.
- Leverage Snowflake's capabilities (e.g., clustering, partitioning, caching) to enhance performance.
- Troubleshoot and resolve performance bottlenecks in ETL processes and data warehouse queries.
Reporting & Analytics:
- Collaborate with the BI team to design and develop dashboards and reports using Power BI.
- Ensure data is clean, accurate, and ready for analysis to support business decision-making.
- Provide support for reporting tools and ensure seamless access to data for users across the organization.
Cloud and Data Infrastructure:
- Utilize AWS, Azure, or Google Cloud Platform for cloud data engineering tasks, such as storage management, compute scaling, and cloud-native services integration.
- Ensure data is secure, compliant with organizational standards, and adheres to industry best practices for cloud deployments.
- Monitor data pipeline and system performance and provide solutions to improve reliability and scalability.
Collaboration & Documentation:
- Work closely with data scientists, data analysts, business analysts, and other stakeholders to ensure business needs are met.
- Document data pipeline architecture, technical specifications, and best practices for future use and compliance.
- Provide mentoring and guidance to junior data engineers and collaborate on knowledge sharing within the team
