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We are seeking an experienced Data Engineer to help build and scale our modern data platform. You will be responsible for designing robust data pipelines, orchestrating workflows, and implementing infrastructure-as-code practices. You will work at the intersection of data engineering, cloud infrastructure, and analytics to deliver reliable, high-quality data products.
Job Responsibility
Design, build, and maintain scalable ELT/ETL pipelines using Microsoft Fabric and DBT
Orchestrate data workflows using Apache Airflow (scheduling, monitoring, alerting)
Implement data quality checks, testing frameworks, and data contract standards
Collaborate with analytics engineers and BI developers to deliver trusted data products
Contribute to data governance, cataloguing, and documentation practices
Requirements
5+ years of data engineering experience in a cloud environment
Strong proficiency with Microsoft Fabric (Lakehouses, Spark, Data Factory, Pipelines)
Hands-on experience with Apache Airflow for workflow orchestration
Experience with DBT (Data Build Tool) for transformations, testing, and documentation
Proficiency in SQL and at least one scripting language (Python preferred)
Familiarity with cloud infrastructure concepts and CI/CD practices
Understanding of data modelling concepts (dimensional, medallion architecture)
Nice to have
Experience with Terraform for provisioning Azure or Fabric resources
Knowledge of Delta Lake / Apache Iceberg table formats
Exposure to Azure DevOps or GitHub Actions for pipeline CI/CD
Microsoft Fabric or Azure Data Engineer certification (DP-203 / DP-700)