Gerente de Dados II (Field Engineering Lead )

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do?

About the Role:

Do you enjoy operating at the intersection of platform engineering, user enablement, and technical leadership? Are you driven by helping teams translate complex data and AI needs into scalable, standardized solutions?

We are looking for a Field Engineering Lead to lead our global team and act as a critical bridge between platform capabilities and real-world usage. This role is centered on driving platform adoption through hands-on engagement with users, ensuring that every solution built aligns with our architectural standards, best practices, and long-term vision.

You will guide a team that works directly with internal customers - responding to adoption tickets, understanding technical requirements in depth, and collaboratively designing solutions that are robust, scalable, and compliant with our data and ML standards.

Key Responsibilities:

• Lead and mentor a global team of Data & ML Field Engineers, fostering technical excellence and a strong service-oriented mindset
• Own the field engagement model, ensuring high-quality handling of adoption requests, technical tickets, and user onboarding journeys
• Guide the team in deeply understanding user needs, translating them into well-architected solutions aligned with platform standards
• Act as a technical escalation point, supporting complex use cases and ensuring consistency in solution design across regions
• Drive platform adoption through hands-on collaboration: solution design sessions, architecture reviews, and iterative problem solving with users
• Define and enforce reference architectures, guardrails, and reusable patterns to ensure scalable and standardized implementations
• Balance user flexibility and platform governance, ensuring adherence to security, data governance, and ML best practices
• Partner with product, platform, and business stakeholders to continuously improve the adoption experience and remove friction
• Establish clear operational excellence across ticket lifecycle, prioritization, and delivery quality
• Promote a culture of pragmatism, quality, and measurable impact in all field engineering activities

What You Bring:

• Proven experience leading Data and/or ML engineering or platform-facing teams
• Strong hands-on background in:
  • Data Engineering (Spark, ETL/ELT, Lakehouse architectures)
  • Machine Learning practices
• Experience working with cloud platforms and orchestration tools (Airflow, ADF, Databricks Workflows)
• Solid understanding of modern data architectures and scalable system design
• Demonstrated ability to translate ambiguous user needs into structured, production-ready solutions
• Strong stakeholder management skills, with the ability to engage both technical and non-technical audiences
• Excellent communication, coaching, and leadership capabilities
• Bachelor’s degree in Computer Science, Engineering, or related field
• Advanced English

Bonus Points For:

• Experience supporting large-scale data platform adoption in global environments
• Familiarity with ML tooling ecosystems (MLflow, Databricks ML, SageMaker, Vertex AI)
• Strong track record in coaching senior engineers and building high-performing teams
• Product mindset and understanding of data platform lifecycle and user journeys

🚀 Why This Role Matters

This is not a traditional engineering management role. It is a field leadership position, where success is measured by how effectively teams adopt and leverage the platform - through well-designed solutions, strong adherence to standards, and meaningful user partnerships.

You will shape how data and AI are built at scale - one interaction, one solution, and one team at a time.

INFORMAÇÕES BENEFICIOS: