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Remote Clickhouse Jobs in Boston, MA (NOW HIRING)

ICONSTAFF

Senior Platform Engineer

Cambridge, MA · Remote

$120K - $200K/yr

Fully remote (HQ Cambridge, MA) Hours: 9-5 EST, with 2-day on-site visits every 6 weeks You'll be ... Exposure to observability tools (Datadog), databases (Cloud SQL, ClickHouse, Bigtable), and cloud ...

Databento

Systems Engineer

Boston, MA · On-site +1

We accommodate 100% remote work, with teammates living around the globe and paid in their local ... Database administration (MySQL, ClickHouse, Redis). * Cloud engineering basics (AWS, GCP -- compute ...

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Remote Clickhouse information

What is the difference between Remote Clickhouse vs Remote Data Engineer?

AspectRemote ClickhouseRemote Data Engineer
Required CredentialsSQL, database management, data warehousingSQL, data modeling, ETL tools, cloud platforms
Work EnvironmentData analytics teams, database administrationData pipelines, infrastructure, analytics teams
Industry UsageData storage, real-time analyticsData integration, pipeline development
Search & Comparison IntentYesYes

Remote Clickhouse specialists focus on managing and optimizing Clickhouse databases for analytics, while Remote Data Engineers build and maintain data pipelines and infrastructure. Both roles require SQL skills and work within data teams, but their core responsibilities differ in scope and focus.

What is a Remote ClickHouse Engineer?

A Remote ClickHouse Engineer is a professional who specializes in managing, optimizing, and troubleshooting ClickHouse databases while working remotely. ClickHouse is an open-source, high-performance columnar database management system used for real-time analytics and big data applications. Remote ClickHouse Engineers are responsible for tasks such as database administration, query optimization, schema design, and ensuring the reliability and scalability of ClickHouse deployments. They often collaborate with development and data teams to implement solutions that leverage ClickHouse's speed and efficiency. Working remotely, they utilize various communication and collaboration tools to stay connected with their teams.

What are the key skills and qualifications needed to thrive as a Remote ClickHouse Developer, and why are they important?

To thrive as a Remote ClickHouse Developer, you need strong SQL expertise, data modeling skills, and experience with large-scale data processing, typically supported by a background in computer science or a related field. Familiarity with ClickHouse, distributed systems, Linux environments, and tools like Docker and version control (e.g., Git) is essential. Excellent problem-solving, self-motivation, and effective remote communication skills are vital for success in this role. These competencies ensure efficient data management, high system performance, and seamless collaboration in distributed teams.

What are the typical challenges faced by a Remote ClickHouse Engineer when managing distributed database clusters?

As a Remote ClickHouse Engineer, one of the main challenges is ensuring consistent performance and availability across distributed clusters, especially when network latency or hardware differences arise. You'll need to proactively monitor replication, sharding, and backup processes, often troubleshooting issues without direct physical access to servers. Collaboration with DevOps and data engineering teams is crucial for deploying updates, scaling infrastructure, and optimizing queries. Adapting to asynchronous communication and clear documentation is also key in a remote environment to maintain smooth operations and knowledge sharing.
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Remote Clickhouse jobs near you
Senior Platform Engineer

Senior Platform Engineer

ICONSTAFF

Cambridge, MA • Remote

$120K - $200K/yr

Full-time

Posted 16 days ago

Job description

Senior Platform/Infrastructure Engineer

Location: Fully remote (HQ Cambridge, MA)

Hours: 9–5 EST, with 2-day on-site visits every 6 weeks


You’ll be responsible for designing, scaling, and maintaining the infrastructure and internal developer platforms that power a real-time learning AI at a seed-stage startup. The role blends infrastructure ownership with platform engineering to enable AI/product teams to ship quickly and reliably.


Key Responsibilities - Infrastructure

  • Maintain production health: performance, reliability, cost efficiency, and security.
  • Manage GCP Kubernetes clusters (GKE), networking, storage, and compute resources.
  • Handle scaling, resource allocation, and high availability for growing customer demand.
  • Refine observability: logs, traces, metrics, dashboards, and alerts.
  • Perform security hardening and cost optimization.


Kep Responsibilities - Platform Engineering

  • Build internal tooling and abstractions for developer productivity.
  • Design CI/CD pipelines using GitHub Workflows and ArgoCD.
  • Provide self-service environments, internal portals, and deployment systems.


Collaboration & Communication

  • Work closely with AI and full-stack teams to optimize system architecture.
  • Explain technical concepts and trade-offs clearly to engineers and non-engineers.
  • Troubleshoot issues across multiple systems (Python, JavaScript, SQL).


Requirements

  • 5+ years in production cloud environments at scale.
  • Strong familiarity with GCP (primary) and some AWS experience.
  • Experience with Kubernetes (GKE), node pools, and memory-intensive jobs.
  • Working knowledge of CI/CD systems (GitHub Workflows + ArgoCD).
  • Exposure to observability tools (Datadog), databases (Cloud SQL, ClickHouse, Bigtable), and cloud services.


Skills & Qualities

  • Strong analytical and problem-solving ability.
  • Clear, collaborative communication.
  • Curiosity and ownership mentality.
  • Fluent in reading/debugging code across Python, JavaScript, SQL.


Technical Stack

  • Cloud: GCP (primary), AWS (secondary)
  • Kubernetes: GKE, multiple node pools
  • CI/CD: GitHub Workflows + ArgoCD
  • Data: Cloud SQL, ClickHouse, Bigtable, GCS, Dataflow
  • Networking: Cloudflare Workers, Durable Objects, WebSocket communication
  • Monitoring: Datadog
  • Environments: Production, Staging, Integration, Development