The posting
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)
Core Responsibilities
1. Data Engineering & Pipelines
- 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
2. Data Architecture
- Design and maintain data lakes / lakehouse architectures
- Implement medallion architecture (bronze, silver, gold)
- Define reusable data models for analytics and AI
3. Analytics Enablement
- Build dimensional and analytical models
- Support Power BI semantic models
- Ensure data usability for reporting and dashboards
4. Azure Platform Implementation
- Configure and manage Azure data services
- Handle storage, compute, orchestration, and security
- Ensure production-ready deployments
5. Data Quality & Testing
- Implement: Data validation rules Pipeline testing (unit + integration) Monitoring and alerting Logging and error handling
Required Skills (Senior Level)
- Strong experience with: Python (data engineering) PySpark Advanced SQL
- Hands-on with: Azure Data Factory ADLS Gen2 Databricks / Synapse / Microsoft Fabric Git workflows
- Experience with: Delta Lake / lakehouse architectures Medallion architecture Power BI (DAX + semantic modeling)
Nice to Have
- CI/CD for data pipelines
- Azure Key Vault
- Data governance / cataloging
- Performance optimization in Spark or Power BI
- Experience in distributed teams
Language Requirements
- English: B1–B2 minimum
- Spanish: Native / Fluent
Working Model
- Remote (full-time dedication expected)
- Freelance / contractor (AOR model possible)
- Long-term collaboration opportunity



