Data Engineering Manager

We are seeking a Data Engineering Manager to lead a team of data engineers in building high-quality, scalable data products and infrastructure. In this hybrid role, you'll balance people management with technical delivery-mentoring engineers, guiding solution design, and collaborating across teams to deliver data systems that support analytics, data science, and operational needs.

This role is ideal for an experienced data engineer or tech lead who is ready to take the next step into engineering management and enjoys blending hands-on support with strategic execution.

If you're excited by this challenge and want to work within a dynamic company, then we'd love to hear from you.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

Team Management & Growth
Lead a team of data engineers through coaching, mentorship, and technical guidance
Support individual career development and performance feedback, creating growth opportunities for your team
Foster a collaborative, inclusive, and high-performance team culture

Technical Oversight & Delivery
Guide the design and implementation of scalable data pipelines, platforms, and data products
Review architecture and code, provide technical direction, and help resolve complex engineering challenges by being hands-on when needed
Ensure delivery of high-quality, reliable solutions aligned with business goals and engineering best practices

Cross-Functional Collaboration
Partner with product managers, data scientists, analysts, and business stakeholders to understand requirements and prioritize work
Translate business needs into actionable engineering detailed plans and ensure timely delivery of key projects
Communicate clearly across technical and non-technical teams to align on priorities and progress

Operational Excellence
Promote operational stability and reliability of data pipelines and systems through monitoring, alerting, and incident response
Advocate for high standards in data quality, governance, and compliance by collaborating with platform and data governance teams
Drive continuous improvement in development workflows and team productivity