Senior Data Platform Architect (GCP) - AI-Ready Data Mesh

Uber Freight

Frisco (TX)

Hybrid

USD 180,000 - 240,000

Full time

12 days ago

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Benefits offered by this job

Health plan

401k match

Parental leave

Mental wellness benefits

Job summary

Uber Freight is seeking a Staff Data Products Engineer & Data Architect to lead the design, governance, and evolution of enterprise-scale data products and modern data platforms from our Frisco office. You will shape data product strategy, drive cloud modernization in GCP, and mentor teams to build scalable, secure data assets that enable AI-powered decision making and business growth.

This role requires deep expertise in data product engineering, data architecture, data governance, and

Qualifications

BSc in CS/IS/Engineering or related field.
10+ years of experience in data engineering or data architecture.
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.

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 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 objectives.
Design modern cloud-native architectures supporting batch, streaming, real-time, and AI-driven workloads.
Create architecture standards, reference models, patterns, and best practices.
Lead architecture reviews and improve scalability, security, and cost optimization.
Ensure alignment across data engineering, analytics, AI, and application teams.
Architect and optimize enterprise data platforms in Google Cloud
Establish cloud-native patterns focused on scalability, resiliency, security, and automation.
Lead cloud modernization and migration initiatives from legacy platforms.
Design AI-ready data architectures supporting ML, Generative AI, and advanced analytics.
Partner with Data Science, AI Engineering, and Platform teams to support model development and ops.
Build architectures for large-scale semantic, structured, and unstructured data processing.
Evaluate emerging AI technologies and provide strategic recommendations.
Establish data governance, metadata, lineage, quality, and compliance standards.
Define data contracts, SLAs, and quality frameworks.
Drive data observability, monitoring, and reliability practices.
Ensure compliance with security requirements.
Collaborate with security and compliance teams on 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 engineers, architects, and data product teams.
Create engineering standards, implementation frameworks, and best practices.
Drive innovation through proofs-of-concept and evaluations.