Principal Data Engineer - Red Hat Sales Data Management (raleigh Office)

Principal Data Engineer

Red Hat's Global Sales Go-To-Market Strategy, Incentives & Data Analytics organization is seeking a Principal Data Engineer to work with a high degree of autonomy to lead the integration, automation, and optimization of complex data solutions. In this role, you will move beyond simple execution to provide technical leadership in data massaging, reconciliation, and architectural design. You will be responsible for building robust data pipelines, ensuring data governance, and collaborating with cross-functional teams to deliver high-quality data products that drive business decisions.

What will you do?

• Advanced SQL Development: Write complex, highly optimized SQL queries across large datasets. You will be the subject matter expert for SQL query tuning and providing performance recommendations to the wider team.
• Python Automation: Utilize advanced Python proficiency (including libraries such as Pandas and NumPy) to clean, massage, and merge raw datasets, automating complex data extraction and loading processes.
• Pipeline Orchestration: Design, schedule, and monitor robust data pipelines using tools like Airflow. You will take ownership of debugging workflows and resolving performance bottlenecks.
• Data Stewardship: Act as a guardian of data integrity. This includes leading initiatives on data governance, compliance, transformation, and validation audits.
• Automated Testing & CI/CD: Develop and maintain automated unit, end-to-end, and integration tests to ensure data accuracy. Participate actively in version control (Git) and CI/CD processes for deploying pipeline changes across environments.
• Cross-Functional Leadership: Partner with Analysts, Engineers, and Operations teams to understand data needs and ensure data accessibility for business stakeholders from the finance and operations organizations.
• Problem Solving: Apply strong analytical skills to translate complex algorithms into efficient software solutions, converting raw data into actionable insights by identifying trends, outliers, and distributions.

What will you bring?

• Experience: 5+ years of experience as a Data Engineer, BI Engineer, or Systems Analyst in an enterprise environment with large, complex data sources.
• Education: Master's degree in Computer Science, IT, Engineering, or equivalent experience.
• Expert SQL: Deep expertise in relational databases (PostgreSQL, MSSQL, etc.) and query optimization.
• Expert Python: Strong programming skills for data querying, cleaning, and presentation, with hands-on experience in data-centric libraries.
• Modern Stack Experience: Working knowledge of DBT (Data Build Tool) and Snowflake data warehousing is highly desirable.
• ELT/ETL Tools: Experience with Fivetran or similar integration tools.
• Autonomy: Ability to manage multiple projects simultaneously in a fast-paced, distributed team environment across different time zones and cultures.
• Troubleshooting: Exceptional logic and reasoning skills to troubleshoot complex data issues.
• Planning: Ability to think strategically about data architecture and project planning.