Principal Data Architect

Job Summary

The Data Development, Insights & Strategy team is a highly focused effort to lead digital-first execution and transformation at Red Hat leveraging data strategically for our customers, partners, and associates.

As a Principal Data Architect, you will play a critical role in building and managing data solutions to support our organization's data-driven initiatives. You will lead a team of data engineers and work closely with data analysts, data scientists, and other stakeholders to ensure data is collected, processed, and made available for analysis.

What will you do?- Review and merge code contributions from others in a given data domain- Design, develop, and maintain data pipelines for data extraction, loading, and transformation (ELT) processes.- Utilize SQL and Python to create ELT processes and collaborate with cross-functional teams to understand data requirements and ensure data pipelines meet business needs.- Data Modeling and Transformation:
- Create and maintain data models using dbt that enable efficient data transformation and reporting.- Collaborate with engineers to ensure data models align with the overall data architecture.- Database Management (Snowflake):
- Manage and optimize Snowflake database systems for efficiency, scalability, and performance.- Work on database schema design, performance tuning, and security within the Snowflake environment.

Team Leadership:
- Lead and mentor a team of data engineers, providing technical guidance, coaching, and support.- Collaborate with other departments and stakeholders to align data engineering efforts with overall business goals.- Promote opensource principles

ELT Development:
- Develop and maintain ELT processes to extract, load, and transform data from various sources into data repositories.- Ensure data quality and accuracy in the ELT processes.

Data Governance and Compliance:
- Implement data governance policies and practices to maintain data quality, security, and compliance with relevant regulations (e.g., GDPR, HIPAA).

Documentation and Best Practices:
- Document data engineering processes, standards, and best practices for knowledge sharing and training.- Promote and enforce coding and data engineering best practices within the team.

Performance Monitoring and Optimization:
- Monitor the performance of data pipelines, databases (Snowflake), and data models, making improvements and optimizations as needed.- Troubleshoot and resolve data-related issues in a timely manner.

What will you bring?- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.- Extensive experience in data engineering, including ELT development, data pipeline management, and data modeling using dbt.- Strong proficiency in Snowflake, including database management, performance tuning, and data security.- Experience with opensource projects and principles- Solid knowledge of data modeling and architecture principles.- Proficiency in Python for data processing and automation.- Leadership and team management skills.- Excellent problem-solving, communication, and collaboration abilities.- Familiarity with data governance, data security, and compliance standards.

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