Core Software Engineer
About the job
- Solid professional software development experience in C++, including experience with Unix/Linux systems.
- Strong knowledge of database internals and design.
- Experience in performance engineering; database experience is ideal, but experience in high-frequency trading, simulation, or real-time data processing is also acceptable.
- Ability to work collaboratively within and across engineering teams.
- Willingness to work with the open-source community and participate patiently and attentively in code reviews.
- Strong problem-solving and production debugging skills.
- High responsibility, ownership, and accountability.
- Contribute to, analyze, and optimize the performance of the core ClickHouse database, including query optimization, distributed query optimization, relational operators such as aggregation and joins, caching, and low-level optimizations such as SIMD instructions.
- Extend existing performance tests and add new tests using real-world or synthetic datasets to ensure database performance does not deteriorate over time.
- Support the Support Engineering team in debugging advanced customer performance issues, including participating in an on-call rotation and external community support channels.
- Collaborate with other teams to assess the performance and reliability impact of new features.
- Work with the open-source community by resolving issues, reviewing and finishing pull requests, and answering questions through email, chats, Google Groups, and external Slack channels.
- Experience with ClickHouse.
- Experience in security, privacy, and compliance.
- Experience with TCP/IP and network programming.
- Experience developing cloud infrastructure services, preferably with Kubernetes.
- Experience giving public talks at technical conferences and meetups.
- Previous contributions to open-source projects.
About the company
ClickHouse builds a fast, scalable database designed for analytics. It provides a column-oriented database system that stores data by column, which speeds up analytical queries and makes it well-suited for OLAP workloads. The software is available as open-source and can be deployed locally or in the cloud, and the company also offers a fully managed ClickHouse service on AWS, Google Cloud, and Azure. This combination gives users a low-cost, easy-to-manage option for large-scale data processing. ClickHouse differentiates itself from many competitors with its high performance on analytical queries, open-source model, and the added option of a managed cloud service. The company’s goal is to help developers and businesses analyze large datasets quickly and cost-effectively by providing a fast, easy-to-use, and scalable data management solution.
Company Size
501-1,000
Company Stage
Late Stage VC
Total Funding
$1.1B
Headquarters
Palo Alto, California
Founded
2021
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Simplify's Take
What believers are saying
- January 16, 2026, ClickHouse raised $400 million at a $15 billion valuation.
- September 22, 2026 run-rate revenue surpassed $350 million across 4,000 customers.
- September 29, 2026 Microsoft added Fabric, OneLake, and BYOC distribution for ClickHouse.
What critics are saying
- ClickHouse is stretching into Postgres, Langfuse, and security, diluting engineering focus.
- Snowflake, Databricks, and Microsoft bundle adjacent workloads into broader platform deals.
- Microsoft Fabric dependence gives Microsoft leverage over ClickHouse's enterprise distribution and roadmap.
What makes Clickhouse unique
- ClickHouse's columnar engine powers sub-second analytics on massive, fast-moving datasets.
- Open-source core plus Cloud, BYOC, and Fabric integrations widen deployment flexibility.
- Customers use ClickHouse for analytics, observability, security, and AI workloads.
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Benefits
Health Insurance
Unlimited Paid Time Off
Flexible Work Hours
Remote Work Options
Stock Options
Home Office Stipend
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↑ 0%2 year growth
↓ -2%ClickHouse 26.9 adds incremental refreshable materialized views, time-limited CREATE TOKEN credentials and boundary-based LIMIT. ClickHouse 26.9 ships 56 new features, adding APPEND INCREMENTAL refreshable views for Iceberg, CREATE TOKEN credentials, LIMIT AFTER/UNTIL, and DISTINCT disk spilling. Verified pipeline | Sources: 2 | Publisher: signed | Contributor: signed | Hash: d9f74eac9d | View Overview. ClickHouse has released version 26.9. According to the ClickHouse release post, the release "contains 56 new features | 135 performance optimizations | and 464 bug fixes." The 26.9 release call slides list the same three counts. The previous spring release was covered in ClickHouse 26.5. What The Machine Herald know. Incremental refreshable materialized views. The release post says ClickHouse 26.9 adds APPEND INCREMENTAL to refreshable materialized views, so that instead of scanning the entire source table on every refresh, ClickHouse processes only the rows committed since the previous refresh. The post says this can be used to copy append-only data into another ClickHouse table or to replicate an event stream from a MergeTree table into an Iceberg data lake. Per the same post, block-number and block-offset columns provide the cursor ClickHouse uses to identify rows committed after the previous refresh. For an Iceberg target, the post says ClickHouse stores the incremental cursor in the snapshot summary, and that if ClickHouse restarts, the next refresh resumes from that position instead of replaying the same events. The post credits Smita Kulkarni as the contributor. CREATE TOKEN. According to the release post, CREATE TOKEN lets a user create a time-limited credential for applications, scripts, CI jobs, and agents without exposing or replacing their main password. The post states that a token never grants more privileges than the user already has and stops working when it expires or if the user is removed. If no VALID UNTIL or VALID FOR is given, the default lifetime is 30 minutes, and ClickHouse displays the token only once. The slides show the syntax CREATE TOKEN VALID FOR INTERVAL 7 DAY GRANTS (SELECT ON default.sales);. The post credits Alexey Milovidov. LIMIT with boundary conditions. The release post says 26.9 extends LIMIT with boundary conditions that start and stop output based on values in the ordered result stream, "a capability that, to our knowledge, is not currently available in any other database." That is ClickHouse's own claim and was not independently verified. AFTER includes the row that matches its condition, UNTIL stops before its matching row, and ALL applies the boundary each time the condition matches. One example in the post, LIMIT 5 AFTER status >= 500, starts at the first server-error response in a log table and returns five requests. The post credits Zakhar Kravchuk and Nihal Miaji. Performance and other changes. * Min, max and count from statistics: the post says ClickHouse stores minimum and maximum values for numeric-like columns in each data part, and as of 26.9 can use those statistics to answer min, max, and count queries without reading the underlying column data. The use_statistics_for_min_max_aggregation setting disables the optimization. * DISTINCT spilling: setting max_bytes_before_external_distinct lets DISTINCT spill its intermediate state to disk. The post says ClickHouse automatically enables external DISTINCT when max_bytes_ratio_before_external_distinct is set to 0.5, meaning spilling starts when it reaches half of the memory available. * JSON and time types: the post says 26.9 adds bracket syntax for accessing paths in a JSON value, and allows Time values as offsets when adding to or subtracting from DateTime values. * PromQL: the post says 26.9 expands PromQL support with more functions, additional Prometheus HTTP API endpoints, and direct SELECT queries against TimeSeries tables. PromQL and the TimeSeries table engine are in private preview on ClickHouse Cloud. What The Machine Herald don't know. * Both cited sources are published by ClickHouse itself; no independent benchmarks or third-party evaluation of the new features were found. * The sources reviewed do not state how the incremental refresh mode behaves for update- or delete-heavy source tables, since the described use case is append-only data. * No source reviewed gives performance figures for the min/max/count statistics optimization or the DISTINCT spilling path.
ClickHouse expands collaboration with Microsoft, bringing Fabric integration, deeper onelake interoperability, and enterprise deployment flexibility. BARCELONA, Spain - ClickHouse, the company behind the open-source, real-time analytical database that has become the data layer for the AI era, today at The European Microsoft Fabric + SQL Community Conference announced a significant expansion of its strategic collaboration with Microsoft. The announcement encompasses four major milestones: the launch of the native ClickHouse workload...
ClickHouse has expanded its collaboration with Microsoft, introducing four major integrations at The European Microsoft Fabric + SQL Community Conference in Barcelona. The company launched a native ClickHouse workload for Microsoft Fabric, now available in public preview, enabling sub-second query response times within the Fabric platform. The expansion includes general availability of OneLake read capabilities for Apache Iceberg tables, public preview of OneLake write functionality, and availability of ClickHouse Bring Your Own Cloud (BYOC) through the Microsoft Marketplace. BYOC allows organisations to run ClickHouse Cloud within their own Azure tenant whilst maintaining full data control. The integrations enable customers to query and write data directly from OneLake without duplication or separate ETL pipelines. ClickHouse serves over 4,000 customers including DoorDash, Meta, Tesla, and Visa, providing real-time analytical database solutions for AI, observability, and data warehousing applications.
QuaerisAI Now Connects to ClickHouse. Shikha Pilley Sep 23, 2026 QuaerisAI now connects to ClickHouse, helping teams turn fast-moving data into trusted business answers. The integration lets business users ask plain-English questions of ClickHouse data while keeping answers tied to certified definitions, source data, and governance controls. Let AI summarise and analyse this post for you: Real-time data is becoming central to how modern teams operate. Marketing teams need to understand campaign movement. Finance teams need to review usage and metering data. Risk and operations teams need to investigate unusual activity. Product teams want to bring analytics closer to customers. ClickHouse gives teams a high-performance foundation for querying large volumes of fast-moving data. QuaerisAI adds the governed question layer on top. With the ClickHouse integration, business users can ask questions in plain English and receive answers that stay connected to certified definitions, source data, and governance controls. The goal is to make real-time data easier to access, explain, and trust across the business. For many organizations, the challenge is not that the data does not exist. The challenge is that access to that data often depends on SQL, dashboards, or data team support. A marketer may want to know which campaigns underperformed this week. A finance user may need to review usage data behind billing. A risk team may want to investigate unusual patterns. An executive may need a current answer for a board discussion. These questions should not always require a new dashboard or a manual reporting request. QuaerisAI helps close that gap by translating plain-English questions into governed queries that run against ClickHouse. Answers are mapped through QuaerisAI's semantic layer, so teams can work from consistent definitions instead of recreating metric logic for every request. That governance layer matters. Natural-language analytics can make data easier to access, but enterprise teams also need control over how answers are produced. Metrics need to be defined consistently. Answers need to remain traceable to source. Business users need confidence that the number they are using has the right context behind it. The QuaerisAI and ClickHouse integration is designed for teams that need both speed and trust. ClickHouse supports the real-time analytics layer for high-volume data. QuaerisAI helps business users ask questions, understand answers, and trace results back to certified definitions and source data. This combination can support use cases across real-time marketing analytics, usage-based pricing and metering, anomaly investigation, embedded customer-facing analytics, and executive reporting. For ClickHouse customers, QuaerisAI expands the way real-time data can be used across the business. More teams can ask questions directly. Data teams can reduce repetitive reporting requests. Business users can move from raw event data to governed answers with less friction. Real-time analytics becomes more useful when it is accessible to the teams making decisions every day. With QuaerisAI on top of ClickHouse, fast-moving data can become trusted business answers.
ClickHouse appoints Mike Scarpelli, former Snowflake and ServiceNow CFO, to Board of Directors. Sep 22, 2026 · 4 minutes read Veteran finance leader who guided three companies through IPOs joins ClickHouse as it surpasses $350 million in annualized revenue SAN FRANCISCO - TUESDAY SEPTEMBER 22, 2026 - ClickHouse, Inc., the company behind the leading database for AI, today announced the appointment of Michael Scarpelli to its Board of Directors. Scarpelli most recently served as Chief Financial Officer of Snowflake, and previously held the CFO role at ServiceNow and Data Domain, leading each company through its initial public offering. He will serve as an independent director and chair the board's Audit Committee. Scarpelli joins ClickHouse during a period of growth that is unusual even by the standards of the current AI cycle. The company has surpassed $350 million in run-rate revenue, up from roughly $200 million at the end of 2025. Scarpelli joins ClickHouse as more than 4,000 customers, including DoorDash, Ramp, Meta, Tesla, Cisco and Visa, build the applications that define their businesses on infrastructure that does not force a choice between speed, scale, and cost. The company was valued at $15 billion in a Series D earlier this year and extended to include institutional investors J.P. Morgan Private Capital, BDT & MSD Partners, Craft Ventures, and 20VC. As well as individual investors Marco Argenti and Fred Warner. ClickHouse now employs nearly 800 people across 27 countries, with plans to reach 1,000 by year-end, and derives more than half of its revenue from outside the United States. "Bringing Mike onto our board is a statement about the kind of company we are building. He has scaled consumption businesses through some of the largest software IPOs in history with a discipline around unit economics that is rare at growth stage," said Aaron Katz, co-founder and CEO of ClickHouse. "Customers choose ClickHouse because it comes down to price and performance, and we win on both. We ingest and query data at a speed and efficiency no other technology can match, and the value compounds as workloads and use cases grow. As AI agents become the dominant consumers of data, that advantage will only widen. Our job now is to build a world-class enterprise motion on that foundation without losing the developer-first mindset and efficiency that got us here, and Mike is the right person to help us do it." Over a career spanning more than three decades, Scarpelli has helped generate more than $100 billion in shareholder value. "Every generation of infrastructure has a company that redefines the category, and for real-time and agentic workloads that company is ClickHouse," said Scarpelli. "Enterprises are drowning in data tools, and every CFO and CIO I know is trying to consolidate onto fewer platforms that can do more. It is a hard market to win with hundreds of options, and most vendors solve one problem. ClickHouse started with real-time analytics and is now taking on more of the data estate, from data warehousing and observability to agent observability and transactional workloads, on infrastructure that is faster and dramatically more efficient than what it replaces. The expansion I see in this customer base is unlike anything I have seen in my career. Aaron, Yury, Alexey, and the ClickHouse team have paired a category-defining product with a business model built for durability, and I am excited to help them build a generational company." Scarpelli's appointment is part of a deliberate build-out of ClickHouse's finance and governance capabilities, including the 2025 hire of Chief Financial Officer Jimmy Sexton, who previously spent six years in finance leadership at Snowflake, including leading investor relations, and earlier held finance roles at ServiceNow. About clickhouse. ClickHouse, Inc. is the company behind ClickHouse, the open-source, real-time analytical database that has become the data layer for the AI era. Built for the speed, scale, and efficiency that modern applications and AI agents demand, ClickHouse lets companies run real-time analytics, data warehousing, observability, AI and agent observability, and transactional workloads. More than 4,000 customers, including DoorDash, Ramp, Meta, Tesla, Cisco and Visa, build on ClickHouse. Headquartered in the San Francisco Bay Area with offices in Amsterdam, London, New York, Singapore, Sydney, and Tokyo, ClickHouse is backed by investors including Dragoneer Investment Group, Khosla Ventures, Coatue, Altimeter Capital, Index Ventures, Benchmark, J.P. Morgan Private Capital, BDT & MSD Partners, Craft Ventures and 20VC. Learn more at clickhouse.com.