Manager, Data Engineering

Iru•Miami, FL

About The Position

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. 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.

Requirements

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

Nice To Haves

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

Responsibilities

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
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
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