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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Medtronic Inc. - **Location:** Los Angeles County, CA, United States - **Salary:** $88,800.0 - $133,200.0 - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Algorithm Design, Amazon Web Services, Systems Engineering, Big Data, Databases, Data Governance, Data Integrity, Database Development, Digital Assets, Python (Programming Language), Machine Learning, Software Engineering, SQL Databases, Unstructured Data, Cloud Platform System, Snowflake, Data Management, Data Generation - **Published:** September 23, 2026 - **Apply:** https://www.dice.com/job-detail/e1236cc2-40a9-45f0-af7b-02937af7e33c ## About the Role * Bachelor's degree with 2 years of relevant experience OR Master's degree * Experience working with and manipulating large-scale datasets in either academic or industry settings * Experience with data-focused programming language (Python or SQL preferred) * Ability to manipulate, organize, and prepare data from multiple sources. * Experience using AI tools in professional, academic, or research environments., * Medical imaging experience. * AWS or cloud-based infrastructure experience. * Experience with Snowflake or similar data platforms. * Exposure to AI, machine learning, or data science environments. For Baccalaureate degrees earned outside of the United States, a degree that satisfies the requirements of 8 C.F.R. 214.2(h)(4)(iii)(A) is required. ## Description At Medtronic CST, we bring together innovative technologies that empower surgeons and improve outcomes in complex spine and cranial procedures. Check us out on LinkedIn: Medtronic CST Within the Research and Technology (R&T) organization, the team develops the data, infrastructure, and processes that enable advanced algorithms, as well as artificial intelligence (AI) and machine learning (ML) capabilities across future product portfolios. The function partners closely with systems engineering, software engineering, clinical, regulatory, marketing, and data science stakeholders to establish scalable data foundations that support algorithm development, validation, and product readiness. This role is responsible for building and managing the data foundations required to support advanced algorithms, as well as AI and ML development across surgical planning, navigation, and robotics programs. The Data Engineer will lead data acquisition, annotation operations, quality processes, and data governance activities while partnering with cross-functional teams to ensure data assets are scalable, compliant, traceable, and fit for algorithm development and validation. * Lead the activities of data creation and data acquisition; design and execute robust data collection strategies. * Manage annotation and labeling partners and clinical experts for data annotations to needed scale and quality. * Work closely with AI and Product Development teams to define the required data for development of state-of-the-art algorithms. * Contribute to data quality and integrity to ensure the database is well organized and easily accessible. * Maintain and improve data reliability and quality. * Utilize data development and management tools including AI tooling. * Work closely with algorithm developers, test engineers, and Legal and Regulatory departments to assess data compliance. * Work with external and internal providers to manage the R&D database. * Support engineers in R&D data acquisition needs, including designing data collection. * Coordinate with clinical teams on collection of data in clinical trials. * Help inform research and development decisions with data-focused analytics and inputs. * Support other programs and initiatives as assigned. Primary Responsibilities * Lead data acquisition, curation, and preparation activities to support research and product development programs. * Design and implement data collection strategies, protocols, and workflows for clinical, laboratory, internal, and external data sources. * Manage internal and external annotation programs and partners to deliver high-quality labeled datasets at scale. * Establish and maintain data quality standards, validation processes, and governance practices to improve reliability, integrity, and traceability. * Partner with researchers, software engineers, and algorithm developers to define data requirements for artificial intelligence and machine learning initiatives. * Support database administration, organization, and accessibility of structured and unstructured datasets used across development programs. * Collaborate with Legal, Regulatory, and Clinical stakeholders to ensure datasets meet compliance, licensing, privacy, and documentation requirements. * Generate data-driven analyses, metrics, and recommendations that inform research, development, and technology investment decisions.