Senior Project Manager leading the management of roads and highways engineering projects at Arcadis. Coordinating multidisciplinary teams to deliver innovative transportation solutions.
About the role
- Engineering Manager leading a data engineering team at Chainalysis, focused on cloud infrastructure and AI adoption. Overseeing data pipelines and promoting engineering excellence.
Responsibilities
- 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
Requirements
- 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 discussion, and ask meaningful questions in a design review
- A 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
- Strong execution habits: you create and maintain project timelines, know when things are off track before your team tells you.
- The 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
- Collaborative instincts and experience working cross-functionally with Product, other engineering teams, and leadership in a fast-moving environment
- An interest in or curiosity about cryptocurrency and blockchain technology — we can help you learn, but the curiosity has to be genuine
- A 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.
Benefits
- Offers Equity
- Offers Bonus
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