Level

Stripe

Specialist Solutions Architect, Data

Stripe is hiring a Specialist Solutions Architect, Data for a remote role open to applicants in United States. Level rates it ; you can apply on Stripe.

Level's read on this job

  • On Level's scale, this solutions architect role is Little AI ●○○○: aI is not part of the work.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include Databricks, Snowflake and BigQuery.
  • Level classifies it as a senior role.
  • Level lists 720 other open roles at Stripe.

AI in this role

Specialist Solutions Architect for Data products at Stripe, advising enterprise clients on data architecture, warehousing, and analytics integrations.

databrickssnowflakebigqueryredshiftlookertableausigmametabase
data-warehousingetleltdata-pipelinessql

Who We Are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About The Team

Specialist Solutions Architects (SSA) are domain experts aligned to specific Stripe solutions and customer buying centers. We have in-depth knowledge of specific solution offerings and a deep understanding of customer challenges. We align with specialist product sellers on deals, advise the broader pre-sales team on complex opportunities, support pipeline development and revenue attainment, serve as an advisor on go-to-market sales plays, and provide critical insights to our product and engineering teams.

What You'll Do

You will collaborate closely with sales and pre-sales teams to drive pipeline and revenue targets, while also educating the product and engineering teams on market trends and strongly influencing the product roadmap. You will develop deep relationships with senior customer business leaders and grow Stripe's solution offerings with new and existing customers. As a subject matter expert, you will scale the broader organization by creating reusable assets and coaching others on complex, high-value opportunities.

Responsibilities

  • Act as a subject matter expert on Stripe's Data products (data pipelines/export, revenue and reconciliation reporting, and analytics tooling) to accelerate opportunities
  • Demonstrate a deep understanding of how businesses warehouse and model payments and revenue data — data pipelines into Snowflake, BigQuery, Redshift, and Databricks; ETL/ELT patterns; and how that data feeds financial reporting, reconciliation, and BI
  • Conduct deep discovery of customers' existing data architecture, warehouse, and reporting stack to architect solutions that align Stripe's Data capabilities with their analytics and finance requirements
  • Advise customers on how to design for complexity: multi-entity and multi-currency reporting, custom data models, integration with existing BI tools (Looker, Tableau, Sigma, Metabase) and ERP/GL systems, and data freshness/latency requirements
  • Create and share best practices and reusable assets such as reference architectures to enhance the quality and efficiency of the broader sales and pre-sales organizations
  • Partner closely with the Data product sales team and actively drive opportunities for Stripe's largest customers, leading solution strategy and owning key customer relationships
  • Serve as a "Voice of the Customer" to drive product and feature request prioritization
  • Identify product, industry, implementation, and competitive trends, and provide actionable insights to product stakeholders and sales to influence Stripe's Data product roadmap
  • Act as an escalation point to drive complex technical issues to resolution with Stripe's engineering team
  • Represent the technical health of the business on quarterly sales forecast calls and highlight deal blockers with proposed solutions
  • Support marketing events including executive briefings, conferences, user groups, and trade shows

Who You Are

You're capable of engaging in both business-level and technical conversations at multiple levels of a customer organization, including finance, data, and engineering leadership. You enjoy working on products that require deep technical understanding combined with business context, and you're as comfortable in a warehouse schema as you are in a revenue conversation with a CFO. You're excited to become an expert and to share that knowledge broadly.

If you meet the minimum requirements below, we encourage you to apply — the preferred qualifications are a bonus, not a requirement.

Minimum Requirements

  • 7+ years of experience in a technical sales, pre-sales, or solutions architecture role, with a focus on data platforms, analytics, or financial reporting
  • 3+ years of hands-on experience with data warehousing and pipeline architecture (e.g., Snowflake, BigQuery, Redshift, Databricks) and ETL/ELT tooling
  • Strong understanding of how payments and revenue data maps to financial reporting and reconciliation workflows
  • Experience working with or implementing BI/analytics platforms (Looker, Tableau, Sigma, Metabase, or similar)
  • Strong knowledge of software engineering and API integration patterns, including how data pipelines are built and maintained
  • Exceptional communication, presentation, and interpersonal skills, comfortable explaining complex technical concepts to both technical and non-technical audiences
  • A proven ability to build strong collaborative working relationships with business partners
  • Ability to deal effectively with ambiguity and thrive in an unstructured, fast-moving environment

Preferred Qualifications

  • Experience integrating Stripe or other RESTful APIs into data pipelines or web applications
  • Familiarity with complex reporting scenarios: multi-entity consolidation, revenue recognition data models, or usage-based billing data
  • Experience with SQL at an advanced level and comfort working directly in a customer's data warehouse during discovery
  • Experience as a subject matter expert in financial services, fintech, or a data/analytics vertical
  • Pre-sales experience with Enterprise customers

How we rate this

Specialist Solutions Architect, Data at Stripe rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data WarehousingETLEltData PipelinesSQLDatabricksSnowflakeBigQuery

Also common in solutions architect jobs at this level

Pay

Typical solutions architect job
$168k

This posting doesn't list pay. Use the typical solutions architect figure when pay comes up. See solutions architect jobs

Questions you could be asked

  1. Tell me about a project where data warehousing was part of your work. What did you do?
  2. Tell me about a project where etl was part of your work. What did you do?
  3. Tell me about a project where elt was part of your work. What did you do?
  4. Tell me about a project where data pipelines was part of your work. What did you do?
  5. Tell me about a project where sql was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Data Warehousing, ETL, Elt, Data Pipelines, and SQL. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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