• Design, develop and maintain scalable and robust data pipelines and ETL processes to support HR modernisation • Collaborate with stakeholders to gather data requirements and translate them into effective technical solutions • Lead migration to cloud-based infrastructure and modernise ETL tools and processes • Work with DevOps aspects of data engineering, including infrastructure setup, configuration, and maintenance using Infrastructure as Code (IaC) • Ensure data quality and governance by implementing frameworks for accuracy, consistency, and compliance • Promote best practices in data engineering and stay up to date with emerging technologies • Mentor junior colleagues • Contribute to broader organisational digitalisation and technical innovation

• 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.