832 Enterprise Architect jobs in Oakland,CA

5+ years of experience in Enterprise Account Management, Strategic Sales, or Customer Success, preferably in SaaS, automotive tech, or industrial solutions
Proven track record of managing and expanding high-value enterprise accounts, including upsell, cross-sell, and multi-site deployments
Experience working with OEMs, logistics providers, dealerships, or fleet management organizations
Strong ability to engage and influence complex stakeholder groups, including executives, engineering, and operations leaders
Strategic and consultative mindset, with experience in building and executing account growth plans
Experience leading product demos, pilots, and enterprise implementations from pre-sale through post-deployment
Strong commercial acumen with a data-driven approach to customer performance and ROI
Experience conducting business reviews (QBRs/MBRs) and aligning customer goals to business outcomes
Highly organized with strong project management skills; able to manage multiple complex accounts simultaneously
Technical proficiency with CRM systems and analytics tools
Automotive, OEM, Fleet, or Logistics experience
Bachelor's degree in Business, Engineering, Computer Science, or related field
Travel to customer locations to support onboarding and system training activities
This role involves regular on-site work within dealership environments and requires approximately 60% travel

Astound

Concord, CA 94520

Confidential

San Francisco, CA 94103

Over 10 years of data experience
At least 3 years in senior leadership within high-growth fintech or regulated financial services
Proven expertise in building and scaling enterprise data ecosystems
Strong leadership and communication skills
Technical proficiency in cloud warehouses, modeling, ETL, orchestration, and business intelligence is required
Strong SQL
Familiarity with Python
Experience with AWS data services
Infrastructure as code is essential
Must have ability to oversee data governance, cataloging, lineage, metadata, access controls, and auditability
Must be able to build semantic layers, unified source of truth datasets, and experimentation frameworks
Must be able to develop modern data architecture with real-time pipelines, event streaming, warehousing, and orchestration for analytics and machine learning
Must be able to lead analytics and data science, including business intelligence, self-service analytics, dashboarding, reporting, and risk scoring
Experience in regulated financial services (fintech or similar) is required