Senior Data Engineer

Who you are

• We’re looking for a strong Software Engineer with experience in Data Engineering
• Someone who is proficient in building robust, scalable, maintainable, and thoroughly monitored data pipelines on cloud environments
• BSc. in Computer Sciences
• Strong background as a software engineer with at least 5+ years of hands-on experience with Java, Rust, or Python
• 8+ years in data engineering and data pipeline development on high-volume, low-latency production environments
• Experience working in low-latency, real-time systems processing billions of events a day
• Deep, 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 plus
• Proficiency across the broader data engineering stack: Apache Kafka, Spark, Airflow, Kubernetes, Redis, Snowflake, and caching technologies
• Expert-level SQL and query optimization skills, with a strong emphasis on ClickHouse-specific patterns - materialized views, projections, TTLs, and merge tree tuning
• Experience with monitoring and observability tools (Prometheus, Grafana, or similar), with the ability to define and own operational health metrics for a ClickHouse deployment
• Curiosity, ability to work independently, and a track record of proactively identifying and driving solutions
• Excellent verbal and written communication skills, including the ability to coach and influence engineers across teams in a remote environment

What the job involves

• 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