Engineering Manager, Data Cloud

Stack

Responsibilities

• ▹Lead, coach, and develop a team of 6 engineers spanning streaming, data lakehouse, serving layer, and platform infrastructure
• ▹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
• ▹Coach each engineer toward their next level with specific plans, timely feedback, and active promotion sponsorship
• ▹Champion engineering best practices: design reviews, ADRs, blameless post-mortems, automated testing, and data quality as a first-class citizen
• ▹Manage the on-call rotation and incident response process so reactive work doesn't consume the team's capacity to build
• ▹Build an understanding of the data cloud architecture to ask better questions, anticipate risks, and have credible stakeholder conversations
• ▹Foster a culture of curiosity and continuous learning
• ▹Hire exceptional talent with a focus on diversity and complementing existing strengths
• ▹Drive AI adoption across the team's engineering workflows — development, code review, documentation, and debugging

Requirements

• ▹Experience managing 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 — able to read a Terraform plan and engage meaningfully in a streaming architecture discussion
• ▹A track record of developing people: coaching engineers to promotion, giving hard feedback that led to growth
• ▹Strong execution habits: creating and maintaining project timelines, catching issues before they're off track
• ▹Clear communication — explaining technical decisions to a VP, writing incident summaries, drafting quarterly plans
• ▹Collaborative instincts working cross-functionally with Product, other engineering teams, and leadership
• ▹Genuine interest in or curiosity about cryptocurrency and blockchain technology
• ▹A proactive mindset toward AI-assisted engineering, with hands-on experience using tools such as Copilot, Claude, ChatGPT, or Cursor

Nice to have

• ▹Knowledge of the modern data stack: Spark, Databricks, Kafka, Delta Lake/Iceberg, some Flink and/or StarRocks experience
• ▹Cloud cost optimization and FinOps experience
• ▹Background in blockchain, fintech, or other data-intensive domains
• ▹Experience driving AI adoption within an engineering team
• ▹Hands-on experience with AI coding assistants (Claude Code, GitHub Copilot, Cursor)

Soft skills

About the company

Chainalysis is the blockchain data platform, connecting the movement of digital assets to real-world services. Powered by deep blockchain data and AI, it helps organizations investigate illicit activity, manage risk exposure, and develop innovative market solutions.