Data Engineer
Summary
Build and maintain data pipelines, warehouses, and models in Azure using Microsoft Fabric and ADF to support analytics and reporting.
Job Summary
Design, develop, and maintain data ingestion, transformation, and orchestration pipelines using Microsoft Fabric and Azure Data Factory (ADF). Build and manage ETL/ELT processes for structured and unstructured data sources. Develop and optimize data models, data lakes, and data warehouses within the Azure ecosystem. Integrate data from multiple on‑premises and cloud‑based systems. Monitor, troubleshoot, and optimize data pipelines to ensure reliability and performance. Implement data quality, governance, and security best practices. Collaborate with business analysts, data scientists, and stakeholders to understand data requirements. Develop and maintain technical documentation, data dictionaries, and operational procedures. Support reporting and analytics platforms such as Power BI. Participate in data platform modernization and cloud migration initiatives, implementing improvements.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Minimum 4–6 years of experience in data engineering or related roles.
- Strong experience with Microsoft Fabric, including Data Factory, Lakehouse, Data Warehouse, and Dataflows.
- Hands‑on experience with Azure Data Factory (ADF).
- Proficiency in SQL and data modeling concepts.
- Experience with Azure Data Lake Storage (ADLS), Azure Synapse Analytics, and Azure SQL Database.
- Strong understanding of ETL/ELT design and implementation.
- Experience with REST APIs, data integration, and automation.
- Knowledge of CI/CD practices and version control tools such as Git.
- Strong analytical and problem‑solving skills.
Preferred Qualifications
- Microsoft Azure Data Engineer certification (DP-203) or Microsoft Fabric certification.
- Experience with Python, PySpark, or Spark‑based data processing.
- Experience with Power BI and analytics solutions.
- Knowledge of DevOps and Infrastructure-as-Code practices.
- Experience working in Agile environments.
Technical Skills
- Microsoft Fabric
- Azure Data Factory (ADF)
- Azure Data Lake Storage (ADLS Gen2)
- Azure Synapse Analytics
- Azure SQL Database
- SQL Server
- PySpark / Spark
- Python
- Power BI
- Git / Azure DevOps
- REST APIs
Key Competencies
- Data Integration & ETL/ELT Development
- Data Modeling & Warehousing
- Performance Optimization
- Problem Solving & Troubleshooting
- Stakeholder Management
- Documentation & Knowledge Sharing
- Team Collaboration