Delivery Solutions Architect - Financial Services
Leads post-sale technical strategy and execution for Databricks platform adoption in strategic financial services accounts. Drives onboarding, enablement, and production acceleration of data/AI workloads with 7+ years experience in Data/AI delivery and programming in Python, SQL, or Scala.
About the job
Responsibilities
- Engage with Solutions Architects to understand the full use case demand plan for prioritised customers
- Lead the post-technical win technical account strategy and execution plan for the majority of Databricks use cases within our most strategic accounts
- Be the accountable technical leader assigned to specific use cases and customer(s) across multiple selling teams and internal stakeholders, creating certainty from uncertainty and driving onboarding, enablement, success, go-live and healthy consumption of the workloads where the customer has made the decision to consume Databricks
- Be the first contact for any technical issues or questions related to production/go live status of agreed upon use cases within an account, oftentimes services multiple use cases within the largest and most complex organizations
- Leverage both Shared Services, User Education, Onboarding/Technical Services and Support resources, along with escalating to expert level technical experts to build the right tasks that are beyond your scope of activities or expertise
- Create, own and execute a point-of-view as to how key use cases can be accelerated into production, coordinating with Professional Services (PS) resources on the delivery of PS Engagement proposals
- Navigate Databricks Product and Engineering teams for new product Innovations, private previews and upgrade needs
- Develop an execution plan that covers all activities of all customer-facing technical roles and teams to cover the below work streams:
- Main use cases moving from 'win' to production
- Enablement / user growth plan
- Product adoption (strategy and activities to increase adoption of Databricks' Lakehouse vision)
- Organic needs for current investment (e.g. cloud cost control, tuning & optimization)
- Executive and operational governance
- Provide internal and external updates - KPI reporting on the status of usage and customer health, covering investment status, important risks, product adoption and use case progression - to your Technical GM
Requirements
- 7+ years of experience where you have been accountable for technical project / program delivery within the domain of Data and AI and where you can contribute to technical debate and design choices with customers
- Programming experience in Python, SQL or Scala
- Experience in a customer-facing pre-sales, technical architecture, customer success, or consulting role
- Understanding of solution architecture related distributed data systems
- Understanding of how to attribute business value and outcomes to specific project deliverables
- Technical program, or project management including account, stakeholder and resource management accountability
- Experience resolving complex and important escalation with senior customer executives
- Experience conducting open-ended discovery workshops, creating strategic roadmaps, conducting business analysis and managing delivery of complex programmes/projects
- Track record of overachievement against quota, Goals or similar objective targets
- Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience
- Can travel up to 30% when needed
Skills
Python, SQL, Scala, Databricks, Lakehouse, Data Intelligence Platform, Distributed Data Systems, Solutions Architecture, Cloud Cost Optimization, Technical Program Management
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