Senior Data Engineer

Boston Scientific • Arden Hills, MN

22d • $85,000 - $161,500 • Onsite

About The Position

Boston Scientific's Active Implantable Systems (AIS) R&D organization is seeking a Senior Data Engineer to join our AI Transformation core team and design and build the data pipelines that power our AI-enabled engineering workflows. This is an exciting opportunity to join a growing team that will enable the re-imagining of how work gets done across our R&D engineering functions. You will own data curation, indexing quality and pipeline reliability, ensuring that engineering knowledge — requirements, design history, test data, quality records and more — is current, trusted and AI-accessible. You will work closely with the AI Solutions Architect and AI Solutions Delivery roles to ensure engineering data sources are structured and governed in a way that supports retrieval-augmented generation, evaluation and agentic workflows across AIS R&D, while meeting the data quality, lineage and compliance standards required in a regulated product development environment.

Requirements

• Bachelor's or master's degree in computer science, data engineering, data science or a related technical field.
• Minimum of 7 years' experience designing, building and operating production data pipelines.
• Strong experience with data curation, indexing and data quality frameworks at enterprise scale.
• Experience with modern cloud data platforms (e.g., AWS, Snowflake, Databricks) and ETL/ELT frameworks.
• Advanced SQL skills and experience optimizing large-scale analytical or operational datasets.
• Experience implementing data governance practices, including metadata management, lineage and data quality controls.
• Experience working in a regulated, enterprise-scale environment with security, compliance and quality requirements.

Nice To Haves

• Experience supporting retrieval-augmented generation (RAG), vector databases, embeddings or semantic search.
• Experience building data pipelines that support machine learning, LLM or agentic AI workflows.
• Experience with engineering data sources such as PLM (e.g., Windchill), requirements management or version control systems.
• Familiarity with MLOps/LLMOps practices, including data versioning and pipeline monitoring.
• Experience in health care, life sciences, medical devices or another highly regulated industry.

Responsibilities

• Design and build data pipelines that ingest, curate and index engineering data sources to support AI-enabled workflows.
• Own data curation, indexing quality and pipeline reliability across all in-scope engineering data sources.
• Ensure engineering knowledge — requirements, design history files, test data, quality records and related artifacts — is current, trusted and AI-accessible.
• Define and enforce data quality checks, schemas and governance practices for operational AI systems.
• Partner with the AI Solutions Architect on the context layer, versioned prompt/agent specification library and retrieval architecture.
• Partner with the AI Solutions Delivery role and Enterprise AI/IT on integration patterns across engineering systems (e.g., Windchill, Jira, GitLab, AWS).
• Scale pipeline reliability and indexing coverage as additional workflows move from pilot to production.
• Support evaluation-harness data needs, including test data preparation and data-quality regression checks.
• Contribute to a culture of ownership, experimentation and data-driven decision-making.

Benefits

• The anticipated compensation listed above and the value of core and optional employee benefits offered by Boston Scientific (BSC) – see www.bscbenefitsconnect.com—will vary based on actual location of the position and other pertinent factors considered in determining actual compensation for the role.
• Compensation will be commensurate with demonstrable level of experience and training, pertinent education including licensure and certifications, among other relevant business or organizational needs.
• At BSC, it is not typical for an individual to be hired near the bottom or top of the anticipated salary range listed above.
• Compensation for non-exempt (hourly), non-sales roles may also include variable compensation from time to time (e.g., any overtime and shift differential) and annual bonus target (subject to plan eligibility and other requirements).
• Compensation for exempt, non-sales roles may also include variable compensation, i.e., annual bonus target and long-term incentives (subject to plan eligibility and other requirements).

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree