Solutions Architect - Retail

Description

Solutions Architect (L5), requisition FEQ128R82. You are building a technical specialty (archetype) and are already known in your team for depth in one domain.

The company is a data and AI firm. More than 20,000 organizations worldwide, including 70% of the Fortune 500, use its platform to build and scale data and AI apps, analytics and agents. It is headquartered in San Francisco with 30+ offices around the globe.

The hiring process has six steps: recruiter screen, hiring manager screen, design and architecture interview, live coding assessment, a build, demo and pitch presentation, and a reference check.

Responsibilities

• Own the technical plan for your accounts, from first discovery through production rollout and ongoing usage growth.
• Lead complex design discussions and build scalable, production-ready solutions across data engineering, ML and AI, and real-time analytics.
• Act as a trusted adviser to customer architects, engineering leads and directors.
• Win competitive deals by showing where the platform stands apart, using solutions you build yourself.
• Develop a technical specialty (archetype) and become the team's go-to person in that area.
• Coordinate DSAs, SSAs and partners to deliver full solutions for hard customer problems.
• Give structured feedback on customer needs and competitor gaps to shape product direction.

Requirements

• 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role.
• Strong Python and SQL, with the ability to code live, debug and build solutions on the spot.
• Deep knowledge of distributed data systems: scalable pipelines, streaming, lakehouse patterns and cloud-native data platforms.
• Working proficiency on the company Platform, or the ability to get there quickly, with a developing specialty in one area such as real-time or streaming, ML and AI, data governance or migrations.
• Skill at leading architecture discussions with senior technical people through whiteboarding, design reviews and trade-off analysis.
• Production deployments on AWS, Azure or GCP, covering infrastructure, security and governance.
• A record of driving platform adoption and usage growth within accounts.
• Clear communication that turns complex architecture into business value for technical and executive audiences.
• Bachelor's or Master's degree in computer science, engineering or a quantitative field, or equivalent experience.
• The company certifications (Data Engineer, ML, Platform).
• Experience with competing platforms such as Snowflake, AWS native services or Azure Synapse, so you understand what you are positioning against.
• Background at a data or AI company or a cloud provider.
• Industry domain expertise, for example in financial services, healthcare, retail or media.

Conditions

The pay range below is the expected salary for non-commissionable roles, or on-target earnings for commissionable roles.

Local pay range: $180,000 - $247,500 USD.

Final pay depends on factors such as job-related skills, depth of experience, relevant certifications and training, and work location. The company expects to use the full width of the range.

The total package may include eligibility for an annual performance bonus, equity and the benefits below.

Applicants are considered regardless of protected characteristics; if a role needs access to export-controlled technology or source code, the company decides whether to seek a U.S. government license and may decline an applicant on that basis alone.

Benefits

• Benefits are offered by region, and the company's benefits page lists the details for your location.