Data Engineer

Position: Data Engineer

Salary: 50,000- 55,000

Purpose of the Role and Primary Objectives

• As a Data Engineer, you will play a crucial role in supporting and transitioning the existing BI reporting suite to Power BI, assisting in a data migration project, and utilising Data Bricks.
• This role requires close collaboration with business stakeholders, data engineers, and team members to create effective data models, visualisations, and reports, ensuring a focus on delivery and providing world-class customer support and engagement.

Main Responsibilities

• Understand data modelling, storing, and managing data, including visualization using Power BI.
• Work with languages such as Python or SQL for data processing and manipulation, using SparkSQL/PySpark for Azure Databricks.
• Extract, transform, and load data from different sources into data lakes, specifically using Azure Databricks and Data Factory.
• Build interactive reports, dashboards, etc., using Power BI.
• Design and develop data models for Power BI reports and dashboards.
• Define tables, columns, and relationships based on business requirements.
• Implement custom calculations, measures, and calculated columns using DAX language.
• Experience in creating and implementing Row Level Security (RLS).
• Collaborate with data engineers to ensure data quality and consistency during the ETL process.

Skills

• Stay informed about Power BI updates, features, and best practices by actively participating in the Power BI community.
• Share knowledge and collaborate with other developers.
• Engage and collaborate with stakeholders at various levels, including executives, managers, and end-users.
• Familiarity with Azure Data Factory and Data Bricks.
• Knowledge of SQL, data warehousing, and cloud technologies.
• Understanding of Medallion Architecture for Data Brick with proven experience as a Data Engineer or similar role.
• Proficiency in Power BI Desktop, DAX language, and ETL processes.
• Strong communication and problem-solving skills with the ability to collaborate effectively with cross-functional teams and business stakeholders.
• Knowledge of cloud platforms like Azure, AWS, or Google Cloud Platform (GCP), with Azure preferred.
• Basic understanding of machine learning concepts and using machine learning models for predictive analytics.