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We are looking for a Data Engineer to design and build modern data platforms on Azure. This role focuses on transforming raw data into reliable, scalable, and analytics-ready foundations that support reporting, advanced analytics, and AI-driven use cases.
This is a hands-on engineering role, not just conceptual design. The candidate must be comfortable working across ingestion, transformation, modeling, orchestration, and data quality.
Target profile for this role: Senior Data Engineer (5+ years)
Design and implement ETL / ELT pipelines (batch and optional streaming)
Build transformations using Python, PySpark, SQL
Orchestrate workflows using Azure tools
Integrate data from multiple structured and semi-structured sources
Design and maintain data lakes / lakehouse architectures
Implement medallion architecture (bronze, silver, gold)
Define reusable data models for analytics and AI
Build dimensional and analytical models
Support Power BI semantic models
Ensure data usability for reporting and dashboards
Configure and manage Azure data services
Handle storage, compute, orchestration, and security
Ensure production-ready deployments
Data validation rules
Pipeline testing (unit + integration)
Monitoring and alerting
Logging and error handling
Python (data engineering)
PySpark
Advanced SQL
Azure Data Factory
ADLS Gen2
Databricks / Synapse / Microsoft Fabric
Git workflows
Delta Lake / lakehouse architectures
Medallion architecture
Power BI (DAX + semantic modeling)
CI/CD for data pipelines
Azure Key Vault
Data governance / cataloging
Performance optimization in Spark or Power BI
Experience in distributed teams
English: B1–B2 minimum
Spanish: Native / Fluent
Remote (full-time dedication expected)
Freelance / contractor (AOR model possible)
Long-term collaboration opportunity
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