Senior Data Engineer (Infra)

Solidus Labs; Greater London; On-site; GBP 110,000 - 170,000; Full time

Job summary

Solidus Labs is seeking a senior Software Engineer specialized in Data Engineering to architect and optimize our ClickHouse data layer. You will own cluster sizing, topology and capacity planning for real-time ingestion and batch workloads, while driving data reliability and schema governance.

The role requires deep ClickHouse expertise, strong SQL, and experience coaching teams in a remote environment. You will collaborate with analytics, ML and product teams to improve data models, query

Qualifications

• 5+ years of hands-on software engineering experience.
• 8+ years in data engineering and data pipeline development.
• Proficiency in Java, Rust, or Python.
• SQL expertise with ClickHouse patterns like materialized views, TTLs, and merge trees.
• Experience with monitoring and observability tools (Prometheus, Grafana) and defining health metrics.

Responsibilities

• Design and optimize the ClickHouse data layer for billions-of-events scale.
• Own ClickHouse clusters sizing, topology decisions and capacity planning.
• Establish and improve monitoring, alerting, and observability for ClickHouse.
• Coach engineers across teams on query optimization and data modeling best practices.
• Collaborate with analytics, ML, and product teams to refine schema design and data formats.
• Define and enforce schema versioning and governance within ClickHouse deployments.

Skills

ClickHouse

Data engineering

Java

Python

Rust

Kafka

Spark

Kubernetes

Prometheus

Grafana

SQL

Education

BSc in Computer Sciences

Tools

Prometheus

Grafana

Kafka

Spark

Airflow

Kubernetes

Redis

Snowflake

Job description

• As an ambitious start-up in an extremely dynamic space, we pride ourselves on being independent, accountable, and organized, with a self-starter attitude and a willingness to get our hands dirty with day-to-day work that might fall outside our official scope, while keeping an eye on our goals and the big picture
• Design and optimize the ClickHouse data layer - including table engines, partition strategies, materialized views, and storage policies - to ensure high performance at billions-of-events scale
• Own ClickHouse clusters sizing, topology decisions, and capacity planning across both real-time ingestion and T+1 batch workloads, balancing cost, latency, and throughput
• Drive data reliability and deduplication strategies within ClickHouse, leveraging engine-level features (ReplacingMergeTree, CollapsingMergeTree, etc.) and pipeline-level controls to guarantee data completeness and consistency
• Establish and continuously improve monitoring, alerting, and observability for the ClickHouse layer — covering replication health, merge performance, query latency, and resource utilization
• Serve as the internal ClickHouse authority, coaching engineering teams across the organization on query optimization, data modeling best practices, and efficient use of ClickHouse-specific constructs
• Act as the primary liaison with the ClickHouse vendor team - triaging issues, incorporating product feedback, evaluating new features, and translating vendor guidance into actionable improvements for our deployment
• Collaborate with downstream consumers (analytics, ML, product) to understand access patterns and continuously refine how data is stored and served — improving query performance, schema design, and data formats for diverse client needs
• Define and enforce schema versioning and governance standards within the ClickHouse environment, ensuring schema evolution does not compromise pipeline reliability or consumer compatibility

Someone who is proficient in building robust, scalable, maintainable, and thoroughly monitored data pipelines on cloud environmentsWe’re looking for a strong Software Engineer with experience in Data EngineeringBSc. in Computer SciencesExperience with monitoring and observability tools (Prometheus, Grafana, or similar), with the ability to define and own operational health metrics for a ClickHouse deploymentStrong background as a software engineer with at least 5+ years of hands-on experience with Java, Rust, or Python8+ years in data engineering and data pipeline development on high-volume, low-latency production environmentsProficiency across the broader data engineering stack: Apache Kafka, Spark, Airflow, Kubernetes, Redis, Snowflake, and caching technologiesExpert-level SQL and query optimization skills, with a strong emphasis on ClickHouse-specific patterns - materialized views, projections, TTLs, and merge tree tuningCuriosity, ability to work independently, and a track record of proactively identifying and driving solutionsDeep, hands-on ClickHouse expertise - including cluster architecture, table engine selection, replication, sharding, and query optimization. Experience engaging with the ClickHouse vendor team or community is a strong plusExperience working in low-latency, real-time systems processing billions of events a dayExcellent verbal and written communication skills, including the ability to coach and influence engineers across teams in a remote environment