Full-Time

Delivery Solutions Architect

Financial Services

Posted on 9/12/2024

Databricks

Databricks

5,001-10,000 employees

Unified data platform for analytics and AI

Data & Analytics
Enterprise Software
AI & Machine Learning

Compensation Overview

$115.8k - $204.8kAnnually

+ Annual Performance Bonus + Equity

Senior, Expert

United States

This is a hybrid role requiring in-office presence.

Category
Solution Engineering
Sales & Solution Engineering
Required Skills
Python
SQL
Scala
Databricks
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
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

Databricks provides a platform that combines the features of data lakes and data warehouses, referred to as lakehouse architecture. This platform allows organizations to efficiently manage, analyze, and gain insights from their data. It caters to a diverse clientele, including data engineers, data scientists, and business analysts in sectors like finance, healthcare, and technology. Databricks streamlines data ingestion, management, and analysis through automated ETL processes, secure data sharing, and high-performance analytics. Additionally, it supports machine learning and AI workloads, enabling users to build and deploy models at scale. The company operates on a subscription-based model, generating revenue from platform access and professional services. The goal of Databricks is to empower organizations to leverage their data effectively for better decision-making.

Company Stage

Growth Equity (Venture Capital)

Total Funding

$3.9B

Headquarters

San Francisco, California

Founded

2013

Growth & Insights
Headcount

6 month growth

9%

1 year growth

38%

2 year growth

79%
Simplify Jobs

Simplify's Take

What believers are saying

  • Increased demand for data lakehouse solutions boosts Databricks' market potential.
  • Growing interest in open-source tools aligns with Databricks' acquisition of Tabular.
  • Expansion of AI applications in key sectors enhances Databricks' client base.

What critics are saying

  • Increased competition from companies like Snowflake threatens Databricks' market share.
  • Integration challenges with Tabular could lead to operational inefficiencies.
  • Rapid AI model development may attract ethical and regulatory scrutiny.

What makes Databricks unique

  • Databricks offers a unified platform combining data lakes and warehouses, known as lakehouse.
  • The platform supports collaborative data science and machine learning workflows.
  • Databricks integrates with various cloud services for seamless data management and analysis.

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Benefits

Extended health care including dental and vision

Life/AD&D and disability coverage

Equity awards

Flexible Vacation

Gym reimbursement

Annual personal development fund

Work headphones reimbursement

Employee Assistance Program (EAP)

Business travel accident insurance

Paid Parental Leave

INACTIVE