Data Engineer II

BlueLabs is hiring a Data Engineer II to advance and modernize its data platform, improve data quality, and migrate legacy systems to a Kimball/star schema architecture. The role owns production data engineering work, establishes modeling and hygiene practices, and provides technical guidance to teammates.

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
• Other duties as assigned

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