Job Description

Role Overview

We are looking for an experienced Data Engineer to design, build, and manage modern cloud data platform solutions. This is a greenfield opportunity to build a scalable Azure data platform from the ground up, creating the technical foundation for AI-ready data, reporting, analytics, and data-driven decision-making across the organisation.

The adecuado candidate will have strong hands-on experience with Microsoft Fabric, Azure Data Factory, Azure Data Lake Storage, Python, and SQL, along with a solid understanding of modern data engineering and lakehouse architecture.

Key Responsibilities

Design, implement, and continuously improve end-to-end data platform solutions using Microsoft Fabric, Azure Data Factory (ADF), and Azure Data Lake Storage Gen2 (ADLS Gen2).

Build scalable and reliable ETL/ELT pipelines to ingest, process, transform, and integrate data from multiple source systems.

Develop modern lakehouse solutions using Medallion Architecture, including Bronze, Silver, and Gold data layers.

Build and manage Microsoft Fabric Lakehouses,



Warehouses, and Dataflows to support analytics and reporting requirements.

Implement automated data quality checks, validation, monitoring, and pipeline testing to ensure data accuracy and reliability.

Develop efficient data models and schemas to support reporting, analytics, compliance, customer insights, fraud detection, and product development.

Collaborate with offshore data engineering teams, providing technical guidance and ensuring delivery against established engineering standards.

Work closely with Business Intelligence teams to understand reporting and analytics requirements and provide reliable, well-structured data solutions.

Contribute to data governance, metadata management, data cataloging, security, and data quality frameworks.

Implement version control and support CI/CD practices for data engineering solutions.

Create technical documentation and provide knowledge transfer and

📌 Senior Data Engineer – Microsoft Fabric (México)
🏢 DYNE
📍 México