BlueLabs is a leading provider of analytics services and technology dedicated to helping partners leverage their data effectively. The Data Engineer II will play a crucial role in enhancing the data platform's quality and scalability, focusing on modernizing data systems and implementing best practices in data hygiene and modeling.
Responsibilities:
- Partner directly with the Director of Data to translate platform vision into engineering execution
- Lead the design and implementation of Kimball-style dimensional models and star schema architectures, migrating legacy data systems to a modern, scalable foundation
- Own and enforce data hygiene standards across the platform — identifying, documenting, and remediating data quality issues proactively
- Design, build, and maintain production-grade data pipelines with a focus on reliability, observability, and maintainability
- Develop and champion best practices for data modeling, transformation, and testing across the engineering team
- Drive the extraction and codification of business logic from existing systems into well-documented, portable, cloud-agnostic layers
- Collaborate with analysts, engineers, and stakeholders to ensure data models meet both current reporting needs and future platform requirements
- Provide technical guidance and mentorship to Data Engineer I team members
- Contribute to architectural decisions and participate in design reviews, bringing a principled, opinionated perspective on platform direction
- Support and improve documentation standards to ensure the codebase and data platform remain well-understood across the team
Requirements:
- 5+ years of experience in data engineering, with a demonstrated track record of owning and delivering complex data platform initiatives
- Deep expertise in dimensional modeling, including Kimball methodology and star/snowflake schema design
- Experience leading or significantly contributing to data warehouse migrations or platform modernization efforts
- Advanced proficiency with SQL and Python; ability to write production-quality, well-tested, maintainable code
- Strong command of dbt, including advanced features such as custom tests, macros, packages, and documentation generation
- Hands-on experience with Snowflake & Redshift and modern data stack tooling
- A systematic, principled approach to data quality — experience implementing data hygiene frameworks, validation pipelines, and monitoring
- Ability to operate with autonomy and drive work forward in ambiguous or evolving problem spaces
- Strong communication skills with the ability to articulate technical decisions to both engineering and non-engineering stakeholders
- Passion for applying technical skills to social impact work and the ability to thrive in a cross-functional, mission-driven team