Data Engineer

As a Data Engineer with 24 years of experience, including at least 1 year of hands-on experience with Microsoft Fabric, your role will involve the following responsibilities:

• Design, develop, and maintain scalable ETL/ELT pipelines using Microsoft Fabric.
• Work with large datasets using PySpark for data processing and transformation.
• Write optimized and efficient SQL queries for data extraction and analysis.
• Develop data workflows and automation using Python.
• Collaborate with cross-functional teams to understand data requirements and deliver solutions.
• Ensure data quality, integrity, and performance across pipelines.

The qualifications required for this role include:

• Hands-on experience with Microsoft Fabric (minimum 1 year).
• Strong proficiency in PySpark, SQL, and Python.
• Experience in building data pipelines and working with large datasets.
• Good understanding of data engineering concepts and best practices.

Additionally, it would be beneficial if you have:

• Knowledge of Data Modeling (Star/Snowflake schema).
• Experience with Databricks.
• Exposure to CI/CD pipelines and DevOps practices.
• Familiarity with DBT and Git.
• Understanding of modern data architectures such as Lakehouse and Medallion. As a Data Engineer with 24 years of experience, including at least 1 year of hands-on experience with Microsoft Fabric, your role will involve the following responsibilities:
• Design, develop, and maintain scalable ETL/ELT pipelines using Microsoft Fabric.
• Work with large datasets using PySpark for data processing and transformation.
• Write optimized and efficient SQL queries for data extraction and analysis.
• Develop data workflows and automation using Python.
• Collaborate with cross-functional teams to understand data requirements and deliver solutions.
• Ensure data quality, integrity, and performance across pipelines.

The qualifications required for this role include:

• Hands-on experience with Microsoft Fabric (minimum 1 year).
• Strong proficiency in PySpark, SQL, and Python.
• Experience in building data pipelines and working with large datasets.
• Good understanding of data engineering concepts and best practices.

Additionally, it would be beneficial if you have:

• Knowledge of Data Modeling (Star/Snowflake schema).
• Experience with Databricks.
• Exposure to CI/CD pipelines and DevOps practices.
• Familiarity with DBT and Git.
• Understanding of modern data architectures such as Lakehouse and Medallion.