Solutions Architect

Stack

Responsibilities

• ▹Own the technical evaluation process for accounts in the sub-250 employee segment - from first technical conversation through POC, architecture sign-off, and onboarding
• ▹Engage directly with data engineers, platform architects, and technical founders to understand use cases, data volumes, query patterns, and infrastructure requirements
• ▹Troubleshoot schema design, ingestion patterns, and integration challenges during evaluation
• ▹Build and deliver reference implementations, POCs, and architecture recommendations
• ▹Partner closely with Commercial AEs to progress and close opportunities
• ▹Advocate for customer needs internally with Product and Engineering
• ▹Contribute to technical playbooks, objection handling guides, and reusable POC assets
• ▹Participate in developer community events, technical meetups, and online forums

Requirements

• ▹Deep technical foundation in data engineering or a closely related discipline (data engineer, software engineer, analytics engineer, or similar hands-on role)
• ▹Comfort with the modern data stack: columnar databases, streaming ingestion (Kafka, Kinesis), cloud infrastructure, SQL-heavy analytics workflows
• ▹Hands-on experience with ClickHouse, DuckDB, Druid, Pinot, BigQuery, Snowflake, or similar is a strong plus
• ▹Some customer-facing experience in pre-sales, technical account management, solutions engineering, or customer success
• ▹An instinct for moving quickly: driving technical evaluations to conclusion and removing blockers
• ▹Strong written and verbal communication, simplifying complex architectural concepts
• ▹Curiosity about the business side of technology
• ▹Ownership mentality, comfortable operating with autonomy

Nice to have

• ▹Hands-on experience with ClickHouse, DuckDB, Druid, Pinot, BigQuery, or Snowflake
• ▹Prior pre-sales or customer-facing experience

Soft skills

About the company

ClickHouse's commercial customers include developer-first, fast-growing companies such as Circle, Flashbots, Blockworks, Cypress.io, Kit, Whop, Coframe, Shaped, and janitorai, which chose ClickHouse because they needed to handle billions of events without slowing down their users.