We are seeking a Fabric Data Engineer to develop and support data pipelines and transformation logic on our data platform. You will build ingestion jobs, author SQL and PySpark notebooks, and run data quality and validation checks across lakehouse and warehouse layers. Working under the guidance of senior engineers and the Fabric Architect, you will assist with monitoring, documentation, and issue triage while building deep hands‑on experience with the Fabric platform.

Responsibilities

- Develop, test, and maintain ingestion and transformation pipelines on Microsoft Fabric (lakehouse and warehouse layers).
- Author clear, maintainable SQL and PySpark notebooks for ETL/ELT jobs and transformations.
- Implement and execute automated data quality and validation checks; investigate and remediate data issues.
- Monitor pipeline health, respond to alerts, and perform first‑line triage and incident investigation.
- Follow platform and engineering standards set by senior engineers and the Fabric Architect; contribute to runbooks and operational documentation.
- Collaborate with data engineers, analysts, and product stakeholders to translate requirements into reliable data solutions.
- Contribute to CI/CD, testing, and deployment processes for data pipelines.
- Continuously improve pipeline performance, reliability, and observability through instrumentation and refactoring.

Requirements





- 5+ years of professional experience in data engineering or a related role.
- Solid experience in Microsoft Azure services, including practical experience with Microsoft Fabric and Azure Databricks.
- Strong proficiency in SQL for data modeling, transformation, and validation.
- Practical experience with PySpark and authoring notebooks for data processing.
- Familiarity with lakehouse architectures and data warehouse concepts (ETL/ELT patterns).
- Experience implementing data quality checks and debugging data issues across pipeline layers.
- Comfortable working with version control (Git), notebooks, and collaborative documentation.
- Good troubleshooting skills and experience with monitoring/alerting for data pipelines.
- Bachelor's degree in Computer Science, Engineering, Data Science or equivalent practical experience.

Nice to Have

- Experience with Delta Lake, table formats, or similar lakehouse technologies.
- Familiarity with orchestration tools (Airflow, Azure Data Factory) or pipeline CI/CD.
- Experience with data testing frameworks (Great Expectations, dbt tests) and unit testing for data code.
- Knowledge of observability tools (Azure Monitor, Prometheus, Grafana) and logging best practices.
- Microsoft Fabric certifications or relevant cloud certifications (Azure).

📌 Fabric Data Engineer (Colombia)
🏢 Adastra
📍 Colombia