Preql: Engineering Manager / Lead Engineer

Breakout Tools

New York (NY)

On-site

USD 150,000 - 190,000

Full time

14 days+

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Job summary

A dynamic tech firm is seeking an Engineering Manager to lead a small team of full-stack engineers. The role involves a balance between leadership and hands-on coding, focusing mainly on data engineering workloads and AI tools integration. The successful candidate will be responsible for team delivery and growth, and will collaborate closely with the CTO and CEO on the product roadmap. Candidates should have over 7 years of experience in software engineering, managing teams, and a strong background in cloud data services. This is an exciting opportunity to shape the future of enterprise data workflows.

Qualifications

  • 7+ years of software engineering experience, focusing on data engineering.
  • Prior experience managing engineers as team lead, EM, or equivalent.
  • Strong product awareness with customer-centricity experience.

Responsibilities

  • Lead and mentor a team of 3-6 software engineers.
  • Own delivery, velocity, and technical quality.
  • Architect data engineering pipelines for customer data.

Skills

Team leadership
Data engineering
Experience with AI codegen tools
Project tracking
Cloud data services (AWS, Snowflake)

Tools

TypeScript
Python

Job description

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
  • 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
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