Key Responsibilities and Roles:

• Responsible for constructing and maintaining data pipelines that extract, transform, and load data from diverse data sources into centralized repositories, such as data warehouses, lakehouses, and databases.
• Implement physical data models to effectively structure and organize data for efficient storage and analysis, while ensuring data integrity optimization.
• Develop processes to transform raw data into a usable format for analysis and reporting purposes, including data cleanup and deduplication.
• Integrate data from disparate sources and ensure data quality and consistency throughout the data pipeline.
• Oversee database management activities, including database design, administration, optimization, and performance enhancement.

Required Competencies:

• Bachelor’s degree in Computer Science, Information Technology, Mathematics, or an equivalent field.
• Minimum of 6 years of hands-on progressive experience in Data Engineering.
• At least 6 years of experience in ETL, ELT, data warehousing, and data modeling.
• At least 3 years of delivering solutions on the Microsoft Azure Platform, with exposure to data solutions and services such as Microsoft Fabric, and Data Factory.
• Proficiency in PySpark or Python, T-SQL scripting and strong technical knowledge of databases.
• Expertise in designing, building, and maintaining data pipelines to extract, transform, and load (ETL) data from various sources into data storage systems such as data warehouses or lakehouses.