AWS Principal Data Engineer
Listed on 2026-06-23
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IT/Tech
Data Engineering -
Engineering
Data Engineering
Additional Location(s): US-CA-Valencia; US-CA-Santa Clara; US-MN-Arden Hills
Diversity
- Innovation
- Caring
- Global Collaboration
- Winning Spirit
- High Performance
Boston Scientific was recognized by Forbes as one of the Best Workplaces for Engineers in 2026, reflecting a culture where engineers do meaningful work.
The role is a senior, hands‑on technical leader and principal individual contributor responsible for designing, building and evolving scalable, reusable AWS data platform solutions. In this role, you will transform governed data into trusted, production‑ready data products that power clinical insights, commercial analytics and AI‑driven innovation.
Operating at the intersection of architecture, engineering execution and governance automation, you will shape how data flows from source systems through ingestion, transformation, quality enforcement and semantic enrichment. You will partner closely with data engineering, platform engineering, security, site reliability engineering (SRE), Dev Ops and governance teams to deliver a modern data platform that operates as a product rather than a collection of siloed solutions.
As a principal‑level individual contributor, you will establish technical direction, define reusable patterns and influence engineering standards across teams through expertise, architecture leadership and mentorship.
Work model, sponsorship, relocationAt Boston Scientific, we value collaboration and synergy. This role follows a hybrid work model requiring employees to be in our local office at least three days per week. Boston Scientific will not offer sponsorship or take over sponsorship of an employment visa for this position at this time. Relocation assistance is not available for this position at this time.
This is a defined‑term position with an anticipated duration of 24 months from the employee’s start date. Based on business needs and individual performance, there may be an opportunity for this role to be considered for regular full‑time employment in the future.
Your responsibilities will include- Design reusable AWS data platform architectures and lead the implementation and migration of complex data pipelines supporting governed ingestion, batch, streaming, change data capture (CDC), event‑driven processing and data product delivery, ensuring validated cutovers and stage‑gated reconciliation.
- Translate governance requirements into automated platform capabilities, including data contracts, schema validation, data quality controls, lineage capture, metadata management and access enforcement.
- Build and maintain infrastructure‑as‑code modules, CI/CD templates and Terraform‑based provisioning frameworks that enable scalable, secure and governed platform deployment.
- Architect and implement platform capabilities for security, observability, resiliency and cost management, including encryption, identity and access management (IAM), telemetry, service‑level objectives (SLOs) and cost attribution.
- Design governed lakehouse and data product patterns using AWS‑native services and open table formats, including Apache Iceberg, to support scalable analytics, AI workloads and enterprise data products.
- Evaluate emerging technologies, document architectural decisions and establish engineering standards that advance platform maturity, scalability and operational excellence.
- Provide technical leadership through architecture reviews, reference designs and mentoring, enabling engineering teams to adopt best practices and deliver predictable, high‑quality solutions.
- Bachelor’s degree in computer science, data engineering, information systems or a related technical field.
- Minimum of 13 years' experience in data engineering, including a minimum of 6 years' experience designing and delivering cloud‑native data platforms in AWS.
- Minimum of 4 years' experience building scalable data platform solutions, including infrastructure‑as‑code, CI/CD, data integration (batch, streaming and CDC) and governance automation such as data contracts, quality controls, lineage and access management.
- Demonstrated expertise with AWS data services, including S3, Glue, Athena, Lambda,…
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