• Ingest, clean, transform, and structure customer and internally generated engineering data for AI training and inference. • Design and build high-quality mechanical components and assemblies in CAD to serve as authoritative ground truth for evaluating and training AI systems. • Produce labeled datasets, reference designs, annotations, exploded views, sequences, and other engineering artifacts that encode real-world reasoning. • Apply engineering judgment to define and assess output quality across datasets. • Continuously refine standards for metadata, annotation, and model quality, maintaining a living “definition of quality” for ME datasets. • Collaborate with Product Managers to shape tooling used for annotation, data correction, model-output review, and pipeline automation. • Provide detailed feedback on tool usability, workflow efficiency, and automation opportunities. • Help develop scalable, repeatable data processes that improve throughput and data consistency. • Partner closely with engineering and research teams to understand model data requirements, failure modes, and areas needing new data. • Influence model behavior by supplying representative engineering examples and ground-truth mechanical designs. • Partner with customer-facing teams to translate domain requirements, industry standards, and customer data schemas into actionable dataset specifications. • Serve as a subject matter expert on mechanical engineering formats, CAD standards, manufacturing practices, and design artifacts. • Generate technical documentation, exploded views, sequences, and annotations that encode engineering reasoning into training data. • Ensure that datasets reflect real-world constraints, DFM (Design for Manufacturing) considerations, material behavior, and industry best practices. • Embed engineering reasoning into training data so that AI systems learn not just geometry or text, but engineering intent. • Work with customers to understand their data sources, schemas, formats, and quality expectations. • Guide customers in preparing high-quality datasets, defining structured schemas, and improving data pipelines. • Support delivery timelines by communicating progress clearly and surfacing risks or issues early. • Review and work with external contractors, ensuring high-quality output and adherence to SOPs.

Role Description This is a Remote Role - Abstracts newly diagnosed cancer cases - Assists with case identification - Performs quality control procedures on data Qualifications - College level curriculum in cancer data management or equivalent education/experience - Upon hire: National Oncology Data Specialist - National Cancer Registrars Association - Preferred Qualifications: - Associate's degree - Coursework/Training in Anatomy & Physiology or completing courses - Experience abstracting newly diagnosed cancer cases - Experience working in an ACoS approved Cancer Registry - Using Cancer Registry software, such as ONCOLog Requirements - Minimum and maximum wage rates are posted for this position - Placement on the wage range will be determined based on relevant job experience and other applicable factors - Additional compensation may be available for this role, such as: - Shift differentials - Standby/on-call - Overtime - Premiums - Extra shift incentives - Bonus opportunities Benefits - Comprehensive benefits package including: - Retirement 401(k) Savings Plan with employer matching - Health care benefits (medical, dental, vision) - Life insurance - Disability insurance - Time off benefits (paid parental leave, vacations, holidays, health issues) - Voluntary benefits - Well-being resources - Learn more at providence.jobs/benefits Company Description Providence Swedish is the largest not-for-profit health care system in the greater Puget Sound area. It is comprised of: - Eight hospital campuses (Ballard, Edmonds, Everett, Centralia, Cherry Hill (Seattle), First Hill (Seattle), Issaquah, and Olympia) - Emergency rooms and specialty centers in Redmond (East King County) and the Mill Creek area in Everett - Providence Swedish Medical Group, a network of 190+ primary care and specialty care locations throughout the Puget Sound We’re dedicated to improving the wellbeing of rural and urban communities by expanding access to quality health care for all.

• Modernizing, integrating, and optimizing Dutch Bros foundational data ecosystem. • Building world-class data platforms that power analytics, machine learning, and AI-driven workflows. • Designing and implementing highly scalable and resilient data infrastructure.

Title: Senior Data Engineer Location: United States Job Description: GiveCampus is the world's leading fundraising platform for non-profit educational institutions. Trusted by millions of donors and 1,300+ colleges, universities, and K-12 schools, our mission is to help advance the quality, the affordability, and the accessibility of education. At our current pace, we will facilitate $100 billion in charitable giving over the next decade–enough money to send more than 1 million students to college, tuition-free. GiveCampus is backed by leading investors including Y Combinator, but we’re also practitioners of Sustainable Growth: we’ve made the Inc. 5000 list of America's fastest-growing private companies each of the last five years and we’ve been profitable nine of the last 10. In 2025, we celebrated a $140 million growth investment that included a major liquidity event for GiveCampus employees–the second in less than three years. Our purpose-driven team of 130+ is located in 30+ states across the US: team members work from anywhere they choose. We have a beautiful 12,000sf office in Washington, DC that is available for people to use whenever they want, and we regularly organize team meet-ups, visit partner institutions, and host retreats in various locations. While we operate at meaningful scale, we’re still small relative to the commercial and social good opportunities in front of us. Every GiveCampus employee plays a meaningful role in shaping what comes next, and we're growing the team in support of our ambitious plans–including a $100 million investment in AI product development. If you believe in the transformative power of education and want to join a fast-growing, mission-driven company, you’ll fit right in. Location: This is a remote-first role based in the U.S. While we embrace flexible, distributed work, we also value in-person connection. Team members are expected to attend multiple company-wide and team-specific onsites throughout the year. We are looking for a thoughtful and highly capable Senior Data Engineer to join GiveCampus and help scale and evolve our data platform. You will sit at the center of our data ecosystem, building the models, pipelines, and semantic layers that power decision-making across the company. As a key member of the team, you’ll partner closely with stakeholders across BI, Product, and Data Science to deliver reliable, high-quality data and unlock new capabilities—including LLM-driven features. You’re someone who enjoys turning complex business needs into elegant data solutions, thrives in a fast-moving environment, and is excited to have a meaningful impact. Responsibilities will include: - Partnering with BI to design, build, and iterate on analytics models in Snowflake using dbt - Owning the end-to-end lifecycle of data models, from intake and development to testing, deployment, and documentation - Translating business requirements into clean, performant SQL and dbt models that enable self-serve reporting - Maintaining and improving our dbt project structure, testing framework, and CI/CD practices - Monitoring pipeline health and serving as a first responder for data quality and freshness issues across Airbyte, Fivetran, Prefect, and Snowflake - Managing existing data integrations and building new pipelines using Prefect for orchestration - Improving data observability and alerting to ensure reliability and adherence to SLAs for business-critical reporting - Building and maintaining semantic models in Snowflake that power LLM-driven product features - Developing evaluation pipelines (including LLM-as-judge patterns) to monitor output quality and prevent degradation - Collaborating with Data Science and ML teams to ensure clean, well-modeled data is available for training and inference workloads - Leveraging AI-assisted development tools to improve speed and efficiency, and identifying opportunities to automate repetitive data engineering tasks What we are looking for: - Strong experience writing production-grade SQL and working with modern data warehouses (e.g., Snowflake) - Hands-on experience with dbt for data modeling, testing, and documentation - Familiarity with data pipeline and orchestration tools such as Prefect, Airbyte, or Fivetran - Experience designing and maintaining reliable, scalable data systems with a focus on data quality and observability - Ability to translate ambiguous business problems into structured data solutions - Comfort working cross-functionally in a fast-paced, collaborative environment - Experience supporting analytics, reporting, and/or machine learning use cases - A proactive mindset with strong ownership and attention to detail Bonus points if you have: - Experience building semantic layers or data models that support AI/LLM applications - Familiarity with evaluation frameworks for LLM outputs (e.g., LLM-as-judge patterns) - Experience implementing CI/CD workflows for data projects - Exposure to data observability tools and best practices - Experience in a SaaS or mission-driven organization - Interest in leveraging AI tools to accelerate development and improve workflows Ready to apply? Be sure to keep an eye on your spam and promotions boxes in case our emails end up there! At GiveCampus, we value diversity and we pledge to foster an environment of support, inclusivity, and learning, both on the job and throughout the application process. In this spirit, we encourage candidates of all backgrounds to apply. GiveCampus is an Equal Opportunity Employer. Applicants and employees are not discriminated against because of race, color, creed, sex, sexual orientation, gender identity or expression, age, religion, national origin, citizenship status, disability, ancestry, marital status, veteran status, medical condition or any protected category prohibited by local, state or federal laws. If you feel like you don't meet all of the requirements for this role, please apply anyways. We know confidence gaps and imposter syndrome often get in the way of connecting with incredible people, and we don't want them to prevent us from meeting you.