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Tech Stack
Tools & technologiesAmazon RedshiftCloudPythonSQL
About the role
Key responsibilities & impact- 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
What you’ll need- 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.
- Other duties as assigned.
Benefits
Comp & perks- Premier health insurance plan
- 401K matching
- Unlimited vacation leave
- Paid sick, personal, and volunteer leave
- 13 paid holidays
- 15 weeks paid parental leave
- Professional development stipend & tuition reimbursement
- Employee Assistance Program (EAP)
- Supportive & collaborative culture
- Flexible working hours
- Remote friendly (within the U.S.)
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringdimensional modelingKimball methodologystar schema designSQLPythondbtdata quality frameworksdata hygienedata pipelines
Soft Skills
communication skillsmentorshipcollaborationautonomyproblem-solvingtechnical guidancedocumentation standardsleadershiporganizational skillscross-functional teamwork
