Data Engineer

• Design, develop, and maintain data pipelines using Microsoft Fabric.

   

• Build and optimize ETL/ELT processes for ingesting, transforming, and loading data from multiple sources.

   

• Develop and maintain data transformation workflows using PySpark.

   

• Work with Lakehouse, Data Warehouse, and Data Factory components within Microsoft Fabric.

   

• Collaborate with business stakeholders, analysts, and data teams to understand data requirements.

   

• Ensure data quality, consistency, and reliability across data platforms.

   

• Monitor and troubleshoot data pipeline performance and resolve issues proactively.

   

• Support data modeling and reporting requirements for analytics and business intelligence initiatives.

   

• Participate in code reviews, testing, and deployment activities.

   

• Stay updated with emerging technologies and best practices in data engineering.

   

Required Skills

• 3–4 years of experience in Data Engineering or related roles.

   

• Hands-on experience with Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse, Notebooks, etc.).

   

• Strong proficiency in PySpark for data processing and transformation.

   

• Good understanding of ETL/ELT concepts and data pipeline development.

   

• Experience working with SQL and relational databases.

   

• Basic understanding of Databricks and Spark ecosystem.

   

• Familiarity with data lakes and modern cloud-based data architectures.

   

• Knowledge of data quality, performance tuning, and optimization techniques.

   

• Experience with version control tools such as Git.