Delivery Solutions Architect (Data & AI)

Databricks; Paris; Hybride; EUR 90 000 - 140 000; Plein temps

Résumé du poste

Databricks is seeking a Delivery Solutions Architect to accelerate adoption and growth across customers, acting as the post-sale technical lead across all Databricks products. You will engage with executives, orchestrate cross-functional teams, and drive onboarding, enablement, and value realization for complex workloads selected by customers.

You will collaborate with Sales, Field Engineering, and PS resources to build plans, manage customer success, and ensure healthy consumption, with a

Qualifications

• 5+ years of delivering technical projects/programs in Data and AI
• Experience in a customer-facing pre-sales, technical architecture, customer success, or consulting role
• Understanding of distributed data systems and how to attribute business value to deliverables
• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent

Responsabilités

• Lead post-technical win account strategy and execution for strategic Databricks use cases
• Be the accountable technical leader across use cases and customers, coordinating multiple selling teams
• Leverage Professional Services and technical experts to deliver PS engagement proposals
• Provide internal and external KPI updates on usage and customer health to the Technical GM

Connaissances

Python

Spark

Databricks

Technical leadership

Pre-sales

Customer engagement

Project management

Formation

Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent

Description du poste

At Databricks, we are on a mission to empower our customers to solve the world's toughest data problems by utilizing the the Databricks Data Intelligence Platform. As a Delivery Solutions Architect (DSA), you will play an important role during this journey. You will collaborate with our sales and field engineering teams to accelerate the adoption and growth of the Databricks platform in your customers. You will also help ensure customer success by increasing focus and technical accountability to our most complex customers who need guidance to accelerate usage on Databricks workloads that they have already selected, helping them maximise the value they get of our platform and the return on investment.

This is a hybrid technical and commercial role. It is commercial in the sense that you will drive growth in your assigned customers and use cases through leading your customers' stakeholders, building executive relationships, orchestration of other focused/specialized teams within Databricks, and creating and driving plans and strategies for Databricks colleagues to build upon. This is in parallel to being technical, with expectations being that you become the post-sale technical lead across all Databricks products. This requires you to use your skills and technical credibility to engage and communicate at all levels with an organisation. You will report directly to a DSA Manager within the Field Engineering organization.

The impact you will have:

• 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
• 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

What we look for:

• 5+ 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, Spark and Databricks (or similar data platform)
• 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