AWS Principal Data Engineer

Boston Scientific was recognized by Forbes as one of the Best Workplaces for Engineers in 2026, reflecting a culture where engineers do meaningful work. This role follows a hybrid work model requiring employees to be in the 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. Relocation assistance is not available. This is a defined-term position with an anticipated duration of 24 months; based on business needs and individual performance, there may be an opportunity for this role to transition to regular full-time employment.

About The Role

The AWS Principal Data Engineer 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. You will operate at the intersection of architecture, engineering execution, and governance automation, shaping 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), DevOps, 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.

Responsibilities

• 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.

Requirements

• 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, MSK, Kinesis, DynamoDB, RDS, Redshift, EMR, Step Functions, DMS, ECS, Lake Formation, and DataZone.
• Production-level experience with Snowflake.
• Strong programming and platform engineering expertise using Python, Terraform, Bash, and distributed data processing frameworks such as Spark and Flink.
• Experience with advanced data architecture and modeling concepts, including knowledge graphs, ontologies, semantic layers, and GenAI-enabled data solutions.
• Demonstrated ability to serve as a principal-level technical leader by establishing standards, influencing architectural direction, and driving adoption across multiple engineering teams.
• Ability to travel up to 10%.

Preferred Qualifications

• Master's degree in computer science, data engineering, or a related technical field.
• Knowledge of modern lakehouse and data governance technologies, including Alation, Atlan, DataHub, Informatica, or Databricks.
• Experience supporting AI/ML platforms, including governed analytical workspaces and model lifecycle management.
• Familiarity with regulated industries such as medical devices, healthcare, or life sciences.

Pay

The anticipated compensation range for this role is $106,800 to $202,900. Compensation will vary based on location, experience, education, and other relevant factors. Non-exempt (hourly) roles may also include variable compensation such as overtime, shift differentials, and annual bonuses. Exempt, non-sales roles may include variable compensation such as annual bonuses and long-term incentives, subject to plan eligibility.

Benefits

Boston Scientific offers core and optional employee benefits, including health, retirement, and wellness programs. For more details, visit www.bscbenefitsconnect.com.