Data Platform Engineer

Data Platform Engineer

About the job: Our global data platform powers analytics, data products, and AI use cases for the world's largest brewer. Built on Azure and centered on Azure Databricks, it serves engineers, analysts, and business teams across zones and functions.

About the Team: We are the bridge between the global data platform team and the people who build on it every day: technical users, data teams, and business stakeholders. The global team ships the platform; we make sure people can actually use it well.

What You'll Do:

• Enable users: Help data engineers, analysts, and business teams develop, migrate, and optimize their pipelines and workloads on the data platform.
• Troubleshoot and deep dive: Investigate bugs and unexpected behavior across Databricks, Spark jobs, pipelines, and storage.
• Train and communicate: Build and deliver trainings, documentation, demos, and announcements.
• Explore user needs: Talk with users, spot pain points, and turn them into concrete feedback for the global platform team.
• Give cost visibility: Build reports and dashboards that help teams understand and reduce platform/cloud costs.
• Automate: Build tools, scripts, and workflows (Python, SQL, GitHub Actions, Airflow).
• Monitor and improve: Use observability tools such as Datadog to catch issues early and improve reliability.

What We're Looking For:

• 2–4 years of experience in Data Engineering, Data Platform, Analytics Engineering, or a similar technical role.
• Solid working knowledge of Python and SQL.
• Experience working with data: tables, databases, transformations, and pipelines.
• Strong problem-solving skills and habits.
• Clear communication skills to explain technical issues to both engineers and business stakeholders.
• Professional working proficiency in English (spoken and written) and Spanish.

Our Stack: Azure Databricks, Apache Spark, Python, SQL, Azure Data Factory, Airflow, Azure Blob Storage / ADLS, GitHub, GitHub Actions, and Datadog.

Location: CDMX