Director, Engineering & Business Systems

Must be CST or EST

The Engineering and Business Systems team works collaboratively across Chainalysis’ Business Automation, Data and Systems organization to ensure that core business systems and platforms enable business policies and operational processes. Our job is to empower employees to do their best work by building the foundational systems and data products that drive business decisions and processes while accelerating Chainalysis’ growth.

As the Director, Business Systems & Platform Engineering, you’ll be at the forefront of positioning our technical teams to thrive in an AI-driven shift to headless, API and MCP-driven business systems architectures. You’ll own the integrated technical roadmap for building out the technology architecture as well as the underlying administration and engineering practices. The ideal candidate brings strong software and data engineering leadership depth and can ramp quickly on the GTM and Finance systems domain. The role will lead a small organization that encompasses platform engineering, data engineering, integration engineering and systems administration.

In this role, you'll:

- Lead the systems and engineering org through a shift from a traditional IT and admin-centric org to one centered around platform and data engineering.

- Own the technical architecture, design, and delivery roadmap across business systems, enterprise data and integrations.

- Directly manage and grow systems and engineering-track managers and direct reports including technical mentorship and career pathing.

- Collaborate with team members to establish and codify standards, style guides, workflows, ceremonies and other engineering and systems practices into a single, coherent operating model that leverages AI and agentic processes.

- Partner with colleagues in Product, Success and Program Management to prioritize and deliver the BADaS roadmap by translating business, process and product requirements into technical scope, staffing, and sequencing decisions.

- Act as the internal technical counterpart to vendors and partners, including reviewing architecture proposals, approving technical designs, and owning technical builds.

- Own security, RBAC, and data-governance posture of BADaS platforms, especially from an audit and access-control risk perspective.

- Partner with engineering leaders across Chainalysis on best practices and to leverage platforms, components, solutions and code-bases that already exist.

We're looking for candidates who have:

- 8+ years of experience in software, platform, or data engineering, including 4+ years managing engineers and engineering managers.

- Strong organizational leadership: hiring, career pathing, and building succession depth across a multi-manager org that currently has real single-point-of-failure risk.

- Comfortable operating in an ambiguous, transformation-in-progress environment.

- Demonstrated ownership of team-based technical architecture and engineering practices: repo management, CI/CD, code review standards, test/regression discipline, etc.

- Experience managing a technically mixed org (engineers, data engineers, and platform/systems administrators) and successfully raising the technical bar of the admin-facing work over time.

- Data-first orientation focused on data architecture and flow

- Strong working fluency in modern, event-based, service-oriented architectures using server-side JavaScript / TypeScript / Node.js http://node.js within a primarily serverless AWS environment.

- Deep experience with REST / GraphQL API architectures, relevant authorization strategies including OAUTH and JWT.

- Familiarity with data engineering fundamentals and infrastructure including SQL, Python, dbt / data modeling, pipeline orchestration, batch vs near-real time ETLs and reverse ETLs, medallion architectures.

- Experience with IaC platforms (e.g. Terraform) for DevOps and cloud infrastructure.

Nice to have experience:

- Modern AI-centric engineering workflows and practices.

- Experience with Model Context Protocol (MCP) and building autonomous AI agents.

- Hands-on experience with graph theory and databases, especially as a context layer for Ai co-pilots, workflows and agents.

- Track record of managing vendors and implementation partners on a complex platform build, including technical design review and sign-off authority.

- Experience with enterprise SaaS platforms used in GTM and/or Finance (e.g. Marketo, Salesforce, NetSuite, Nue, Salesforce Revenue Cloud Advanced, Conga and DealHub) at an architectural and API level.

Technologies we use:

- Python, Node.js

- AWS (Lambda, Step Functions, S3, CloudWatch, VPCs, IAM)

- Workato, Fivetran

- Databricks, Airbyte

- Terraform

- Git, Github

- Salesforce, Netsuite, Workday, Marketo, Clari, Adaptive

- LiteLLM, Claude Code