Solutions Architect - Pacific Northwest
AI summary of the role
Own the technical side of enterprise sales cycles for ClickHouse, designing production-scale architectures and driving migrations off incumbents like Elasticsearch, Splunk, Snowflake, and BigQuery.
What you’ll do
- Own the technical evaluation for enterprise accounts from discovery through POC, architecture sign-off, security review, and first production workload.
- Design for production scale: sizing, sharding/replication, ingestion topology, tiered storage, cost modeling, and failure handling.
- Win competitive displacements against Elasticsearch, Splunk, Snowflake, BigQuery, Druid, Pinot, and homegrown systems using reproducible benchmarks.
- Own migration plans including sequencing, dual-run, validation, and cutover.
What you’ll bring
- Deep technical foundation in data infrastructure (data engineer, platform engineer, software engineer, DBA, or solutions architect).
- Production experience with analytical databases (ClickHouse, Snowflake, BigQuery, Redshift, Druid, Pinot, Vertica) and operating them.
- Distributed systems judgment: partitioning, replication, consistency trade-offs, query execution, and failure modes.
- Fluency across modern data stack: Kafka/CDC, orchestration, object storage, BI tools, and at least one major cloud (AWS, GCP, Azure) at architecture level.
Technologies
ClickHouse · Snowflake · BigQuery · Redshift · Druid · Pinot · Vertica · Elasticsearch · Splunk · Kafka · CDC · AWS
About ClickHouse
Open-source columnar OLAP database and managed cloud for real-time analytics, observability, and AI workloads at petabyte scale.
Series D · 200–500 people
Source and classification
Technical pre-sales · Evidence for this classification:
The Role As an Enterprise Solutions Architect at ClickHouse, you'll own the technical side of the sales cycle for enterprise accounts. You'll engage with data platform engineers, architects, SRE, and the VP who owns the standard — and your job is to design something that satisfies all of them and then prove it at production scale. Getting an enterprise team there usually means moving them off something else, so most of your work is making that migration credible: the architecture, benchmarks run against their own data, and a plan their engineers believe they can execute. This is a role for engineers who want the hard version of the problem: real scale, real constraints, and an incumbent to displace. Prior pre-sales experience helps but isn't required — technical depth is non-negotiable. What You Will Be Doing Own the technical evaluation for enterprise accounts — from discovery
More from the job description
The Role As an Enterprise Solutions Architect at ClickHouse, you'll own the technical side of the sales cycle for enterprise accounts. You'll engage with data platform engineers, architects, SRE, and the VP who owns the standard — and your job is to design something that satisfies all of them and then prove it at production scale. Getting an enterprise team there usually means moving them off something else, so most of your work is making that migration credible: the architecture, benchmarks run against their own data, and a plan their engineers believe they can execute. This is a role for engineers who want the hard version of the problem: real scale, real constraints, and an incumbent to displace. Prior pre-sales experience helps but isn't required — technical depth is non-negotiable. What You Will Be Doing Own the technical evaluation for enterprise accounts — from discovery through POC or competitive bake-off, architecture sign-off, security review, and first production workload. Engage across a wider set of stakeholders than a single team: data platform engineers, architects, SRE, security, and the executive who owns the standard. Design solutions that hold up with all of them in the room. Design for production scale — sizing, sharding and replication strategy, ingestion topology, tiered storage, cost modeling, and what happens when something fails at 3am. Win comp [... source excerpt omitted ...] uery, Druid, Pinot, and homegrown systems, using benchmarks the customer's own team can reproduce. Own the migration plan — sequencing, dual-run, validation, and cutover — so the customer's team can see exactly how they get to production. Clear the security and procurement path: questionnaires, compliance artifacts, network and identity architecture, and BYOC or private deployment requirements. Partner closely with Enterprise AEs to progress and close opportunities — you own the technical win, they own the commercial close. Build the TCO case against the incumbent/competition together. Advocate for customer needs internally with Product and Engineering — you're the voice of t [... source excerpt omitted ...] What You Bring Deep technical foundation in data infrastructure — built through experience as a data engineer, platform engineer, software engineer, DBA, or solutions architect. Production experience with analytical databases (ClickHouse, Snowflake, BigQuery, Redshift, Druid, Pinot, Vertica) and with operating them, not just querying them. Distributed systems judgment: partitioning, replication, consistency trade-offs, query execution, and a felt sense for where things break under load. Fluency across the modern data stack — Kafka and CDC pipelines, orchestration, object storage, BI tools, and at least one major cloud (AWS, GCP, Azure) at architecture level. Experience running
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