Job Description

The Principal Data Engineer sets the technical direction that assists engineers and data engineers to take on large, complex data problems/initiatives. This role has considerable technical influence within the Data and Software Engineering teams at JustGiving. This individual acts as an evangelist for proper data strategy with other teams at JustGiving.

What you'll do:

Maintain and assess a legacy SQL Server-based Kimball-style data warehouse, identifying opportunities for modernization and optimization. Design and build scalable data pipelines and ETL/ELT processes using modern tools and frameworks. Collaborate with peers to define and evolve reusable tools and pipeline patterns that support efficient and consistent data transformation. Partner with product managers, data analysts, and engineering teams to design technical solutions that solve real customer problems. Contribute to the development and implementation of data governance practices, ensuring data sovereignty, privacy, security, and regulatory compliance. Monitor and troubleshoot data workflows to ensure high availability, reliability, and performance. Develop and maintain unit and integration tests for data pipelines to ensure reliability and correctness. Champion a culture of documentation to support maintainability, onboarding, and cross-team collaboration. Continuously challenge the status quo and advocate for improvements in data architecture and engineering practices. Stay current with advancements in distributed computing, data architecture, and emerging technologies.

What you'll bring:

8+ years of experience in data engineering or a related field. Hands-on experience with Spark-based platforms such as Microsoft Fabric or Databricks. Solid understanding of distributed system design patterns and experience contributing to their implementation in production environments. Strong SQL skills and experience with dimensional data modeling (Kimball, star/snowflake schemas). Familiarity with the Microsoft BI stack: SSIS, SSAS, Power BI. Knowledge of data governance, security, and compliance best practices. Proven experience with both batch and real-time data processing architectures and tools. Experience to DevOps practices in a data engineering context. Comfort working independently in ambiguous environments. A track record of delivering high-quality, secure, and operable software solutions. Flexibility to work hours aligned with business priorities when needed.

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