Senior Data Engineer (LATAM)
Senior Data Engineer at Rainforest Alliance (sustainability NGO) building its unified data and AI-ready platform on Databricks, Azure Data Lake Storage Gen2, and Power BI. Day to day: design production pipelines and dimensional models, support Power BI reporting and tenant governance, and matrix-manage a small team of data engineers.
- Compensation
- Not disclosed
- Location
- Distrito Federal, Mexico
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Experience building and operating production data pipelines, ideally on Databricks (or comparable Spark-based platform) and cloud data lake storage (ADLS Gen2, S3 or equivalent)
- SQL and hands-on experience with dimensional modelling (star schema / Bronze-Silver-Gold medallion patterns)
- Experience building the data layer behind BI tools, ideally Power BI, including performant, well-governed semantic models and views
- Python and PySpark for pipeline development and testing
- Able to write clear technical documentation that a non-specialist reader can follow
- Comfortable working to formal sign-off gates (requirements, staging, production) and coordinating with analysts, survey and field teams
- Must be legally authorized to work in Mexico, Guatemala, Peru, Colombia or Brazil
Nice to have
- Experience with survey/ODK-style data collection tools (e.g. Survey123, XLSForms)
- Familiarity with data governance concepts (data catalogues, access control, e.g. Unity Catalog) in a multi-tenant or multi-partner data platform
Full description
POSITION:
Senior Data Engineer
LOCATION:
We will only consider candidates legally authorized to work in the Mexico, Guatemala, Peru, Colombia or Brazil.
WORKPLACE TYPE:
Flexible hybrid working environment
CLOSING DATE:
06 November 2026
JOB LEVEL:
15
POSITION SUMMARY:
At the Rainforest Alliance, we believe in the value of data collected at field and company level. With the increasing update of technologies, the amount of data produced will lead to an exponential amount and growth of available information. Unlocking the value of the information and linking it to informed decision-making will enable our organization in reaching the goal of a world where human and nature thrive in harmony.
Rainforest Alliance is building a Unified Data & AI-ready Platform on Databricks, Azure Data Lake Storage Gen2 and Power BI Premium, using a Bronze/Silver/Gold medallion architecture.
In order to progress to a singular platform, we are looking to onboard additional data engineering capability to support both the existing Azure SQL based services and the new platform, which is in pilot phase, as part of wider improvements to the hours of service that we provide to our global users - A working knowledge of both technologies is therefore required. In addition , to provide escalation cover and time zone management, this role will be responsible for the supervision of a team of ( currently 3) data and data platform engineers.
You will report to the Senior Manager , Enterprise Data Platform.
WHAT YOU WILL DO:
- Pipeline engineering: Design, build and maintain robust , production-grade data pipelines and core platform components on Databricks / ADLS Gen2, following the Bronze/Silver/Gold medallion architecture.
- Dimensional modelling: Translate signed-off requirements into dimensional models and the queries that take consolidated raw data to the dimensional model.
- Platform engineering: Build the generic, reusable functions and production code that reproduce, at scale and across the organisation, the same output as the validated queries; Maintain and continue development of the existing SQL-based environment.
- Reporting: Support the design, development and enhancement of Power BI datasets, reports and dashboards; Provide support to report builders/owners in reviewing and optimising reports and datasets, to ensure accuracy, mantainability and performance.
- Power BI Tenant Admin: Support Power BI Premium lifeycle management processes, including user onboarding/offboarding, governance activities (including obsolete workspace and dataset/report cleanup), and performance monitoring/optimisation.