Data Engineer II

Job Description

This opportunity is for a Data Engineer II to help advance and modernize a data platform through stronger data modeling, better data quality, and scalable engineering practices. The role works directly with data leadership and focuses on migrating legacy systems into a modern Kimball-style dimensional model and star schema architecture.

This position is a key technical contributor role with ownership over complex data platform initiatives, production-grade pipelines, data hygiene standards, documentation, and long-term infrastructure scalability.

What You’ll Do
Partner directly with data leadership to translate platform vision into technical execution.
Lead the design and implementation of Kimball-style dimensional models and star schema architectures.
Migrate legacy data systems to a modern, scalable data foundation.
Own and enforce data hygiene standards by identifying, documenting, and resolving data quality issues proactively.
Design, build, and maintain production-grade data pipelines focused on reliability, observability, and maintainability.
Develop and promote best practices for data modeling, transformation, and testing.
Extract and codify business logic from existing systems into well-documented, portable, cloud-agnostic layers.
Collaborate with analysts, engineers, and stakeholders to ensure data models support current and future reporting needs.
Provide technical guidance and mentorship to junior team members.
Contribute to architectural decisions and participate in design reviews.
Improve documentation standards to keep the platform and codebase clear and maintainable.
Perform other duties as assigned.
Qualifications
5+ years of experience in data engineering with a proven 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 SQL and Python skills, with the 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.
Systematic and principled approach to data quality, including experience with data hygiene frameworks, validation pipelines, and monitoring.
Ability to work autonomously and drive projects forward in ambiguous or evolving problem spaces.
Strong communication skills with the ability to explain technical decisions to both engineering and non-engineering stakeholders.
Interest in applying technical skills to social impact work.
Ability to thrive in a cross-functional, mission-driven team environment.
Benefits
Premier health insurance plan.
401(k) matching.
Unlimited vacation leave.
Paid sick, personal, and volunteer leave.
13 paid holidays.
15 weeks of paid parental leave.
Professional development stipend and tuition reimbursement.
Employee Assistance Program.
Supportive and collaborative culture.
Flexible working hours.