{"schemaVersion":"jobsearcher.job.v1","id":"32ebe0a340ffe67e661fb527","url":"https://jobsearcher.com/jobs/32ebe0a340ffe67e661fb527","canonicalUrl":"https://jobsearcher.com/jobs/32ebe0a340ffe67e661fb527","title":"Engineering Manager, Data Cloud","description":"The engineering team at Chainalysis is inspired by solving the hardest technical challenges and building products that establish trust in cryptocurrencies. We're a global organization that thrives on challenging work and doing it alongside exceptionally talented teammates. Our industry evolves rapidly, and our mission is to build a flexible, AI-driven platform that automates entity resolution, optimizes data labeling pipelines, and creates predictive models that identify illicit patterns before they escalat\r\nOur data and solutions have been used to solve some of the world's most high-profile criminal cases and grow consumer access to cryptocurrency safely. Now, by pairing the industry's most trusted blockchain data with agents that reason, investigate, and act, we help our customers scale their workflows as the cryptocurrency economy becomes increasingly mainstream.\r\nThe Data Cloud team is the analytical data platform at Chainalysis. We build and operate the real-time streaming pipelines (Apache Flink), data lakehouse (Databricks), and cloud infrastructure that power how the world understands blockchain data. Our pipelines process billions of records daily and directly serve customers including some of the largest institutions in crypto. This is a small team with outsized impact: 6 engineers managing petabyte-scale infrastructure\r\nWe're looking for an Engineering Manager who leads through service, not authority. You'll partner with a Staff Data Engineer who drives the technical vision and a team of data engineers who are building and maintaining data pipelines, as well as the data cloud infrastructure. Your job is to create the conditions where every engineer on this team does the best work of their career, by removing blockers, coaching growth, driving crisp execution, and building a culture where curiosity, engineering excellence, and intelligent use of AI are the norm.\r\nIn this role, you'll:\r\nLead, coach, and develop a team of 6 engineers spanning streaming, data lakehouse, serving layer, and platform infrastructure — with genuine curiosity about each domain\r\nServe the team by removing obstacles, shielding them from organizational noise, and ensuring they have what they need to ship\r\nOwn the quarterly plan and sprint-level execution: translate OKRs into milestones with clear owners, timelines, and success criteria — and keep them updated without being asked\r\nCoach each engineer toward their next level, with specific plans, timely feedback, and active promotion sponsorship when the work is done\r\nChampion engineering best practices: design reviews before major changes, ADRs for architectural decisions, blameless post-mortems, automated testing, and data quality as a first-class citizen in every pipeline\r\nManage the on-call rotation and incident response process so that reactive work doesn't consume the team's capacity to build\r\nBuild an understanding of the data cloud architecture — not to design it, but to ask better questions, anticipate risks, and have credible conversations with stakeholders\r\nFoster a culture of curiosity and continuous learning, where engineers explore new technologies, share knowledge, and question assumptions\r\nHire exceptional talent to grow the team with a focus on diversity, raising the bar, and complementing existing strengths\r\nDrive AI adoption across the team's engineering workflows — the team has a mandate for AI adoption, and you'll be expected to be a role model, to champion this, remove friction, and help engineers integrate AI tools into their daily development, code review, documentation, and debugging practices\r\nWe're looking for candidates who have:\r\nManaged a team of 5–10 engineers building data infrastructure, data platforms, or backend systems at scale — with a genuine servant leadership philosophy\r\nA software or data engineering background — you've been a hands-on engineer and can read a Terraform plan, follow a streaming architecture discussion, and ask meaningful questions in a design review\r\nA track record of developing people: coaching engineers to promotion, giving hard feedback that led to growth, and building teams where retention is high because people feel valued and challenged\r\nStrong execution habits: you create and maintain project timelines, know when things are off track before your team tells you.\r\nThe ability to communicate clearly — you can explain a technical decision to a VP, write a concise incident summary, and draft a quarterly plan for your team\r\nCollaborative instincts and experience working cross-functionally with Product, other engineering teams, and leadership in a fast-moving environment\r\nAn interest in or curiosity about cryptocurrency and blockchain technology — we can help you learn, but the curiosity has to be genuine\r\nA proactive mindset toward AI-assisted engineering — you should already be using AI tools (Copilot, Claude, ChatGPT, Cursor, or similar) in your own work and have opinions about how they change engineering workflows, code quality, and team productivity. We're looking for someone who sees AI as a multiplier.\r\nYou might also have\r\nKnowledge of the modern data stack: Spark, Databricks, Kafka, Delta Lake/Iceberg, some experience with Flink and/or StarRocks would be appreciated.\r\nCloud cost optimization experience and FinOps practices\r\nA background in blockchain, fintech, or other data-intensive domains\r\nExperience driving AI adoption within an engineering team — setting expectations, measuring impact, removing barriers to adoption, and evolving workflows as tools mature\r\nHands-on experience with AI coding assistants (Claude Code, GitHub Copilot, Cursor) and an understanding of where they accelerate development vs. where human judgment is irreplaceable\r\nTechnologies we use\r\nStreaming: Apache Flink, Kafka (WarpStream)\r\nLakehouse: Databricks, Delta Lake, Iceberg, DBT\r\nCurrently testing StarRocks as a serving layer\r\nInfrastructure: Terraform, AWS (S3, EC2, EKS, IAM), Kubernetes, Helm\r\nCI/CD: GitHub Actions\r\nObservability: Datadog, PagerDuty\r\nAI Development: Claude Code, GitHub Copilot\r\nLanguages: Java, Python, SQL, HCL\r\nDiversity & Inclusion\r\nWe encourage applicants across any race, ethnicity, gender/gender expression, age, spirituality, ability, experience and more. If you need any accommodations to make our interview process more accessible to you due to a disability, please let us know. We can't wait to meet you.\r\nJ-18808-Ljbffr","company":"Chainalysiscareers","rawCompany":"chainalysiscareers","city":"Ontario","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-05T01:34:52.465Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"11-3021.00","title":"Computer and Information Systems Managers","slug":"computer-and-information-systems-managers"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Engineering Manager, Data Cloud","description":"The engineering team at Chainalysis is inspired by solving the hardest technical challenges and building products that establish trust in cryptocurrencies. We're a global organization that thrives on challenging work and doing it alongside exceptionally talented teammates. Our industry evolves rapidly, and our mission is to build a flexible, AI-driven platform that automates entity resolution, optimizes data labeling pipelines, and creates predictive models that identify illicit patterns before they escalat\r\nOur data and solutions have been used to solve some of the world's most high-profile criminal cases and grow consumer access to cryptocurrency safely. Now, by pairing the industry's most trusted blockchain data with agents that reason, investigate, and act, we help our customers scale their workflows as the cryptocurrency economy becomes increasingly mainstream.\r\nThe Data Cloud team is the analytical data platform at Chainalysis. We build and operate the real-time streaming pipelines (Apache Flink), data lakehouse (Databricks), and cloud infrastructure that power how the world understands blockchain data. Our pipelines process billions of records daily and directly serve customers including some of the largest institutions in crypto. This is a small team with outsized impact: 6 engineers managing petabyte-scale infrastructure\r\nWe're looking for an Engineering Manager who leads through service, not authority. You'll partner with a Staff Data Engineer who drives the technical vision and a team of data engineers who are building and maintaining data pipelines, as well as the data cloud infrastructure. Your job is to create the conditions where every engineer on this team does the best work of their career, by removing blockers, coaching growth, driving crisp execution, and building a culture where curiosity, engineering excellence, and intelligent use of AI are the norm.\r\nIn this role, you'll:\r\nLead, coach, and develop a team of 6 engineers spanning streaming, data lakehouse, serving layer, and platform infrastructure — with genuine curiosity about each domain\r\nServe the team by removing obstacles, shielding them from organizational noise, and ensuring they have what they need to ship\r\nOwn the quarterly plan and sprint-level execution: translate OKRs into milestones with clear owners, timelines, and success criteria — and keep them updated without being asked\r\nCoach each engineer toward their next level, with specific plans, timely feedback, and active promotion sponsorship when the work is done\r\nChampion engineering best practices: design reviews before major changes, ADRs for architectural decisions, blameless post-mortems, automated testing, and data quality as a first-class citizen in every pipeline\r\nManage the on-call rotation and incident response process so that reactive work doesn't consume the team's capacity to build\r\nBuild an understanding of the data cloud architecture — not to design it, but to ask better questions, anticipate risks, and have credible conversations with stakeholders\r\nFoster a culture of curiosity and continuous learning, where engineers explore new technologies, share knowledge, and question assumptions\r\nHire exceptional talent to grow the team with a focus on diversity, raising the bar, and complementing existing strengths\r\nDrive AI adoption across the team's engineering workflows — the team has a mandate for AI adoption, and you'll be expected to be a role model, to champion this, remove friction, and help engineers integrate AI tools into their daily development, code review, documentation, and debugging practices\r\nWe're looking for candidates who have:\r\nManaged a team of 5–10 engineers building data infrastructure, data platforms, or backend systems at scale — with a genuine servant leadership philosophy\r\nA software or data engineering background — you've been a hands-on engineer and can read a Terraform plan, follow a streaming architecture discussion, and ask meaningful questions in a design review\r\nA track record of developing people: coaching engineers to promotion, giving hard feedback that led to growth, and building teams where retention is high because people feel valued and challenged\r\nStrong execution habits: you create and maintain project timelines, know when things are off track before your team tells you.\r\nThe ability to communicate clearly — you can explain a technical decision to a VP, write a concise incident summary, and draft a quarterly plan for your team\r\nCollaborative instincts and experience working cross-functionally with Product, other engineering teams, and leadership in a fast-moving environment\r\nAn interest in or curiosity about cryptocurrency and blockchain technology — we can help you learn, but the curiosity has to be genuine\r\nA proactive mindset toward AI-assisted engineering — you should already be using AI tools (Copilot, Claude, ChatGPT, Cursor, or similar) in your own work and have opinions about how they change engineering workflows, code quality, and team productivity. We're looking for someone who sees AI as a multiplier.\r\nYou might also have\r\nKnowledge of the modern data stack: Spark, Databricks, Kafka, Delta Lake/Iceberg, some experience with Flink and/or StarRocks would be appreciated.\r\nCloud cost optimization experience and FinOps practices\r\nA background in blockchain, fintech, or other data-intensive domains\r\nExperience driving AI adoption within an engineering team — setting expectations, measuring impact, removing barriers to adoption, and evolving workflows as tools mature\r\nHands-on experience with AI coding assistants (Claude Code, GitHub Copilot, Cursor) and an understanding of where they accelerate development vs. where human judgment is irreplaceable\r\nTechnologies we use\r\nStreaming: Apache Flink, Kafka (WarpStream)\r\nLakehouse: Databricks, Delta Lake, Iceberg, DBT\r\nCurrently testing StarRocks as a serving layer\r\nInfrastructure: Terraform, AWS (S3, EC2, EKS, IAM), Kubernetes, Helm\r\nCI/CD: GitHub Actions\r\nObservability: Datadog, PagerDuty\r\nAI Development: Claude Code, GitHub Copilot\r\nLanguages: Java, Python, SQL, HCL\r\nDiversity & Inclusion\r\nWe encourage applicants across any race, ethnicity, gender/gender expression, age, spirituality, ability, experience and more. If you need any accommodations to make our interview process more accessible to you due to a disability, please let us know. We can't wait to meet you.\r\nJ-18808-Ljbffr","datePosted":"2026-08-05T01:34:52.465Z","dateModified":"2026-08-05T01:34:52.465Z","hiringOrganization":{"@type":"Organization","name":"Chainalysiscareers","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Ontario","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"32ebe0a340ffe67e661fb527"},"url":"https://jobsearcher.com/jobs/32ebe0a340ffe67e661fb527"}}