Principal Cloud Data Solutions Architect

Description

Position Summary:

The Principal Cloud Data Solutions Architect is a senior individual contributor and technical leader who remains close to implementation. The role is accountable for turning enterprise data strategy into working platforms, reusable engineering capabilities, production-grade pipelines, and architecture decisions that improve delivery across teams.

This role combines hands-on data engineering leadership with ownership of enterprise cloud data solutions architecture. It designs, builds, and evolves scalable, secure, resilient, and cost-effective data platforms; establishes engineering standards and reusable patterns; and guides teams from architecture through production delivery. Operating with significant autonomy, the role partners with business, data, security, infrastructure, and application teams to modernize the enterprise data ecosystem, deliver trusted data products, and ensure solutions meet strategic, regulatory, operational, and reliability requirements.

Role Specific Essential Functions:

• Define, evolve, and govern modern cloud data solutions architecture principles, standards, reference architectures, and reusable patterns aligned with business and data strategy.
• Design and evaluate end-to-end cloud data solution architectures spanning ingestion, streaming, storage, lakehouse and warehouse platforms, transformation, orchestration, analytics, AI/ML, and data consumption.
• Design, build, and evolve end-to-end cloud data solutions spanning source acquisition, data contracts, batch and streaming ingestion, storage, lakehouse and warehouse platforms, transformation, orchestration, analytical modeling, APIs, and data consumption.
• Own the technical direction and delivery quality of complex data initiatives, ensuring platforms, pipelines, and data products are scalable, resilient, observable, interoperable, secure, compliant, and operable in production.
• Assess cloud data technology options and trade-offs, including performance, scalability, interoperability, security, vendor fit, total cost of ownership, and long-term value.
• Establish and improve engineering practices for testing, deployment, monitoring, incident response, data quality, lineage, service-level objectives, fault tolerance, and cost optimization across production data pipelines and platforms.
• Own critical data domains and their supporting pipelines end to end, from source-system engagement and data acquisition through modeling, delivery, operational support, and continuous improvement.
• Partner with business, analytics, data governance, security, application, and platform teams to translate domain needs into governed data products, APIs, shared datasets, and trusted self-service capabilities.
• Identify and lead opportunities to modernize and simplify the data ecosystem through cloud-native services, reusable ingestion and transformation frameworks, configuration-driven data pipelines, data mesh and data product practices, platform consolidation, automation, and legacy-data migration.
• Serve as a cloud data solutions architecture thought leader and mentor, guiding architecture reviews, promoting data engineering best practices, and influencing teams without direct authority.
• Shape cloud data platform and capability roadmaps by anticipating emerging technologies and practices, including real-time data, open table formats, semantic technologies, data observability, FinOps, and AI-ready architecture.

Role Specific Expectations and Qualifications:

• Anticipates internal and external business issues and recommends product, process, or service improvements, including opportunities to modernize cloud data platforms, engineering frameworks, governed data products, semantic layers, and data consumption capabilities.
• Leads high-risk, complex initiatives across the cloud data ecosystem from technical strategy through implementation and operational adoption.
• Analyzes complex business and data problems, makes sound architectural and engineering trade-offs, and delivers recommendations that improve scalability, reliability, delivery speed, data trust, and cost.Exercises independent judgment in methods, techniques and evaluation criteria to work on significant and unique issues involving cloud data solutions architecture, platform capabilities, data integration, modeling, governance, security, scalability, and cost.
• Expert level knowledge in functional area and broad understanding of multiple disciplines. Applies innovative technical or industry knowledge to modern data solutions architecture and analytics practices. Communicates frequently with leadership.
• Acts independently to determine methods and procedures and may supervise the activities of others. Works autonomously under general guidance and serves as a hands-on technical leader for cloud data solutions architecture and engineering.
• Guides cross-functional teams on architecture standards, reference patterns, data contracts, engineering frameworks, semantic-layer approaches, modernization decisions, and production-readiness expectations. Manages multiple processes or programs and establishes operational plans.

Education & Experience:

• Required Education: Bachelor's degree in computer science, engineering, mathematics, information systems, or a related field; equivalent relevant experience may be considered.
• Required Experience: 10+ years of data, software, or technology experience, including 5+ years architecting and implementing enterprise data and analytics solutions on AWS or an equivalent public cloud platform.
• 7+ years designing, building, and operating modern data platforms and distributed data systems using technologies such as SQL, NoSQL, data lakes, lakehouses, cloud data warehouses, Spark, Kafka, and cloud-native batch and streaming services.
• 5+ years of hands-on software and data engineering experience using SQL and at least one modern programming language, such as Python, Java, or Scala, with demonstrated use of version control, automated testing, continuous integration and delivery, infrastructure as code, and code-review practices.
• 5+ years leading complex, large-scale, cross-functional data or cloud initiatives and working directly with internal or external customers and senior stakeholders.

Qualifications & Skills:

• Extensive experience architecting, building, and operating enterprise-scale data and analytics solutions on AWS or an equivalent public cloud platform, including hands-on implementation across data ingestion, transformation, orchestration, storage, modeling, platform engineering, migration, governance, and related technology domains.
• Demonstrated experience building and operating highly available, distributed data ingestion and processing systems at scale, including performance tuning, failure recovery, schema evolution, data quality controls, lineage, observability, and cost management.
• Strong ability to conceptualize modern data solutions architecture, data product, information-model, and semantic-layer patterns and translate them into actionable designs and implementation roadmaps.
• Deep understanding of cloud-native data platforms and end-to-end data solutions architectures, including data lakes, lakehouses, warehouses, batch and streaming pipelines, data modeling, APIs, metadata, data quality, observability, security, governance, and performance optimization.
• Proven skill in evaluating cloud data technologies and solution options from technical, operational, security, interoperability, vendor, and financial perspectives, including performance and FinOps considerations.
• Demonstrated ability to lead technical workstreams and cross-functional project teams, influence technology and data decisions, drive alignment, and communicate complex cloud data solutions architecture concepts to business, engineering, security, governance, and executive audiences.
• Strong analytical, problem-solving, troubleshooting, and decision-making capabilities, with the ability to provide technical guidance throughout delivery and balance scalability, resilience, governance, security, performance, delivery speed, cost, and long-term architectural outcomes.
• Experience working independently on highly complex cloud data problems with broad organizational impact, leading cross-functional teams through platform modernization, and developing data and analytics migration strategies from current-state assessment through implementation.
• Certification/License: Relevant cloud architecture, cloud data engineering, or data management.

Location: Hillsboro, OR | Marlborough/Chelmsford, MA

Target Compensation: $164 - $197K + Annual Bonus

Schedule: Mon- Friday : 8am- 5pm (Hybrid)

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.