Manager, Data Engineering

About Iru   Iru is the AI-powered security & IT platform used by the world’s fastest-growing companies to secure their users, apps, and devices. Built for the AI era, Iru unifies identity & access, endpoint security & management, and compliance automation—collapsing the stack and giving IT & security time and control back.   Iru is backed by some of the smartest investors in tech—General Catalyst, Tiger Global, Felicis, Greycroft, and First Round Capital. In July 2024, Iru raised $100 million from General Catalyst, valuing the company at $850 million. Customers include Cursor, Vercel, Lovable, Replit, and Mercor, and Iru partners with industry leaders such as ServiceNow and AWS. Iru was named to Forbes’ America’s Best Startup Employers 2025 list for employee engagement and satisfaction. The Opportunity: We're looking for an Engineering Manager to lead this team. This is a player-coach role: you'll manage and grow the team while staying hands-on with technical work yourself. You should expect to spend ~40–60% of your time designing, building, and reviewing pipelines, models, and infrastructure alongside the team. You'll report to the Director of Data and partner directly with stakeholders across the business to ensure our data platform keeps pace with the company's growth. This role is high-leverage. The systems you build and the decisions you make will shape how the entire company—and its AI capabilities—understands its products, customers, and performance. About the Team: The Data Engineering team owns the infrastructure and pipelines that power data-driven decisions across the company. We ingest, transform, and deliver centralized data from every product in our portfolio—making it possible for Data Science, Analytics, Finance, Revenue, and our product engineering teams to move fast and trust what they see. Our work is foundational to the company's AI and machine learning initiatives. The quality, freshness, and structure of the data we deliver directly determines what's possible for the models and systems built on top of it. If you want to create leverage for AI at scale, this is where it starts. Our stack includes Kafka, Airflow, Snowflake, dbt, Python, SQL, AWS. We're at an inflection point: the foundation has been built, and now we need leadership to drive the next chapter—modernizing our architecture, raising the bar on data quality, and scaling how we partner with the rest of the org. How You'll Make a Difference Day to Day:

Set technical direction

Drive architectural improvements to how we ingest, transform, and serve data—improving latency, reliability, and data freshness across the platform

Strengthen our transformation layers with clear ownership, data quality checks, and well-defined contracts between stages

Improve our data modeling practices so downstream teams can query confidently

Lead and grow the team

Manage, mentor, and develop a nimble team of data engineers

Build a culture of ownership, quality, speed, and continuous improvement

Create clarity around priorities, ship cadence, and how the team operates

Partner across the org

Work upstream with product engineering to influence how data models are designed in application databases—so they work well with centralized data workflows from day one

Serve as the primary technical point of contact for stakeholder requests, ensuring projects are scoped and architected before work begins

Build strong relationships with teams across the company to understand their needs and deliver data they can trust

We’d love to hear from you if you have:

5+ years of experience in data engineering, with at least 2 years in a leadership or management role

Strong hands-on experience with modern data tools

Deep understanding of data modeling and pipeline architecture patterns

Experience designing and operating reliable data pipelines at scale

Ability to switch between strategic planning, people leadership, and hands-on technical contribution

Clear communication skills—you can translate between technical teams and business stakeholders

Ability to think through problems from the ground up

Required to work on-site 3x a week in our Miami office (Coral Gables).

Nice to haves, but NOT required:

Experience with event-driven architectures, CDC, or streaming technologies

Background in B2B SaaS, especially with multi-product data complexity

Familiarity with data contracts or other patterns for managing upstream schema changes

Experience partnering with application teams to influence source system design