Staff Data Architect

Uber Freight•Chicago, IL

4d•$157,000 - $192,000•Hybrid

About The Position

We are seeking a highly experienced Staff Data Products Engineer & Data Architect to lead the design, development, governance, and evolution of enterprise-scale data products and modern data architecture platforms. This role combines deep expertise in Data Product Engineering, Data Architecture, Google Cloud Platform (GCP), and modern data management principles to enable data-driven decision making and AI-powered business capabilities. As a senior technical leader, working out of our Frisco office you will define architectural standards, establish data product strategies, drive cloud modernization initiatives, and mentor engineering teams in building scalable, secure, reliable, and reusable data assets. You will collaborate across business, engineering, analytics, AI/ML, and platform teams to deliver high-value data products that accelerate innovation and business growth. You will lead critical evaluations of new technologies and drive the architectural decisions that bridge the gap between data and complex business needs.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or related field.
10+ years of experience in Data Engineering, Data Architecture, or related disciplines.
5+ years designing and implementing cloud-native enterprise data platforms.
Proven experience building large-scale Data Products and Data-as-a-Service capabilities.
Experience leading enterprise architecture initiatives across multiple business domains.

Nice To Haves

Master's degree in Computer Science, Information Systems, Engineering, Data Science, or related field.
Google Professional Data Engineer Certification.
Google Professional Cloud Architect Certification.
Experience with Generative AI implementation at enterprise scale.
Experience designing multi-cloud and hybrid-cloud architectures.
Hands-on experience with Data Mesh and modern data product operating models.
Experience implementing enterprise metadata and governance platforms.
Experience supporting AI, machine learning, and advanced analytics initiatives in large organizations.

Responsibilities

Lead the design, development, and lifecycle management of enterprise data products using product-oriented operating models.
Define and implement reusable, scalable, and governed data products across business domains.
Establish standards for data product discoverability, ownership, interoperability, and consumption.
Partner with business stakeholders to translate business requirements into scalable data solutions.
Drive adoption of Data Mesh, Data Fabric, and domain-driven data ownership frameworks.
Define KPIs and success metrics for data product adoption, quality, reliability, and business value realization.
Develop and maintain enterprise data architecture roadmaps aligned with strategic business objectives.
Design modern cloud-native architectures supporting batch, streaming, real-time, and AI-driven workloads.
Create architecture standards, reference models, patterns, and best practices.
Establish enterprise data modeling strategies including conceptual, logical, and physical models.
Lead architecture reviews and recommend improvements in scalability, performance, security, and cost optimization.
Ensure architecture alignment across data engineering, analytics, AI, and application teams.
Architect and optimize enterprise data platforms in Google Cloud
Establish cloud-native architecture patterns focused on scalability, resiliency, security, and automation.
Lead cloud modernization and migration initiatives from legacy data platforms.
Design AI-ready data architectures supporting Machine Learning, Generative AI, and advanced analytics initiatives.
Partner with Data Science, AI Engineering, and Platform teams to support model development and operationalization.
Build architectures supporting large-scale semantic, structured, and unstructured data processing.
Evaluate emerging AI technologies and provide strategic recommendations.
Establish enterprise-level data governance, metadata, lineage, quality, and compliance standards.
Define data contracts, data product SLAs, and quality frameworks.
Drive implementation of data observability, monitoring, and reliability practices.
Ensure compliance with regulatory and organizational security requirements.
Collaborate with security and compliance teams to implement data protection strategies.
Act as a trusted advisor to executive leadership and senior stakeholders.
Provide technical leadership across multiple engineering teams.
Lead architecture review boards and technical design sessions.
Mentor senior engineers, architects, and data product teams.
Create engineering standards, implementation frameworks, and operational best practices.
Drive innovation through proof-of-concepts and technology evaluations.