Engineering Manager, Data Cloud

职位要求 / 描述

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 escalate. Our 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. The 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 We'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. In this role, you’ll: - Lead, coach, and develop a team of 6 engineers spanning streaming, data lakehouse, serving layer, and platform infrastructure — with genuine curiosity about each domain - Serve the team by removing obstacles, shielding them from organizational noise, and ensuring they have what they need to ship - Own 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 - Coach each engineer toward their next level, with specific plans, timely feedback, and active promotion sponsorship when the work is done - Champion 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 - Manage the on-call rotation and incident response process so that reactive work doesn't consume the team's capacity to build - Build an understanding of the data cloud architecture — not to design it, but to ask better questions, anticipate risks, and have credible conversations with stakeholders - Foster a culture of curiosity and continuous learning, where engineers explore new technologies, share knowledge, and question assumptions - Hire exceptional talent to grow the team with a focus on diversity, raising the bar, and complementing existing strengths - Drive 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 We’re looking for candidates who have: - Managed a team of 5–10 engineers building data infrastructure, data platforms, or backend systems at scale — with a genuine servant leadership philosophy - A software or data engineering background — you've been a hands-on engineer and can read a Terraform plan, follow a streaming architecture dis

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