About the Role

We’re looking for an Engineering Manager to lead our core product engineering team. You'll manage a small team of full-stack engineers while staying hands-on with the codebase—roughly an even split between leadership and individual contribution. This role reports directly to both our CTO and CEO.

Your work will focus on data engineering workloads, both AI-powered and human-powered, and the analytics and reporting platform. As we’re building an agentic data system, we expect you to bring experience shipping production systems with modern AI codegen tools (Claude Code, Codex CLI, or similar). Team growth is on the horizon—you may be building out additional headcount within 6 months.

What You’ll Do

Leadership

Manage, mentor, and grow a team of 3-6 software engineers (mostly full-stack)
Own team delivery, velocity, and technical quality
Partner with CTO and CEO on roadmap, prioritization, and resourcing
Build hiring pipelines as the team scales
Ensuring systems of record (project tracking, code quality) continuously up-to-date

Technical

Write and review production (currently TypeScript and Python, depending on product area), using spec- and test-driven development practices
Architect data engineering pipelines that ingest, clean, and transform customer data
Integrate AI codegen tools into team workflows and production systems
Contribute to our agentic data cleaning and data layering features as they evolve

Requirements

7+ years of software engineering experience, including hands-on data engineering
Prior experience managing engineers (team lead, EM, or equivalent)
Strong product awareness and demonstrated work around customer-centricity
Production experience with public-cloud data services (AWS, Snowflake) or equivalent
Hands-on experience using CLI-forward AI codegen agents (Claude Code, Codex CLI, Aider, or similar) in production workflows
Strong opinions on how to integrate AI tooling into engineering team practices
Availability during US Eastern working hours

Nice to Have

Experience building analytics or BI platforms
0→1 Experience: Evidence of manifesting ideas into product
Background in agentic AI systems or LLM-powered automation
Familiarity with data quality, transformation, or semantic layer tools
Startup experience (Series A–B stage)
Compliance Background: SOC 2, audit trail requirements, or regulatory data handling

What Makes This Role Special

You’ll be leading a team that supports how AI transforms enterprise data workflows. This includes expanding our existing tools and solutions, as well as creating entirely new interaction patterns between humans and data systems.

Impact: Your code will directly determine whether finance teams can trust AI with their most critical data

Innovation: Work at the cutting edge of agentic AI applied to real business problems

Preql

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