Azure Data Engineer (Databricks, Spark, dbt, SQL Server)

6+ months contract

Job Description

We are seeking an experienced Azure Data Engineer to design, develop, and maintain scalable data pipelines and analytics solutions. The ideal candidate will have hands‑on experience with Databricks, dbt, Apache Spark, Python, Azure Data Factory, SQL Server, and Power BI, with knowledge of SSIS/SSRS being an added advantage.

Key Responsibilities

• Design, build, and optimize ETL/ELT data pipelines using Azure Data Factory and Databricks.
• Create and maintain data transformation models using dbt.
• Write optimized SQL queries, stored procedures, and database objects in SQL Server.
• Develop Python scripts for data ingestion, transformation, and automation.
• Build and maintain data warehouses and data lakes.
• Develop dashboards and reports using Power BI.
• Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
• Collaborate with business stakeholders, analysts, and developers to deliver data solutions.
• Implement data quality, governance, and security best practices.
• Maintain technical documentation and support production deployments.

Required Skills

• Strong experience with Databricks.
• Hands‑on experience with dbt.
• Strong knowledge of Apache Spark (PySpark).
• Proficiency in Python.
• Experience with Azure Data Factory.
• Experience creating reports and dashboards in Power BI.
• Understanding of data warehousing concepts and ETL/ELT processes.
• Experience with Git and CI/CD practices.

Preferred Skills

• Experience with SSIS and/or SSRS.
• Experience with Azure Synapse Analytics.
• Knowledge of Delta Lake, Unity Catalog, and Azure DevOps.
• Familiarity with Agile/Scrum methodologies.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 3–8+ years of experience in Data Engineering or Business Intelligence.
• Microsoft Azure certifications are a plus.