Data Engineer

Project Description

This project is to architect and develop customers' business Intelligence Reporting portfolio, by doing the transformation of existing BI stake technology to PowerBI and Azure technology. As Data Engineer you'll be working alongside data architects to take data throughout its lifecycle - acquisition, exploration, data cleaning, integration, analysis, interpretation and visualization. You will be creating the pipeline for data processing, data visualization, and analytics products, including automated services, and APIs.

Responsibilities

• As Data Engineer you'll be working alongside data architects to take data throughout its lifecycle - acquisition, exploration, data cleaning, integration, analysis, interpretation and visualization.
• You will be creating the pipeline for data processing, data visualization, and analytics products, including automated services, and APIs.
• Ingest data sources into our data management platforms
• Structure data into a scalable and easily understood architecture
• Work in a multi-disciplined team where you'll turn data discoveries and ideas into models and insights. You'll find how to leverage the data and the models to create and improve products for our customers, in lean development cycles.
• Be able to implement/build methodologies as well as (understand how to) scale them together with the businesses;
• Maintain a good, current and demonstrable knowledge of adjacent applications and market developments both for inspiration and for benchmarking the concepts.

Requirements

• Hands-on business intelligence development or data engineering experience;
• Extensive ETL experience;
• Good exposure to data warehouse design and data lake concepts and practices;
• Exposure to working in a Microsoft Azure Data Platform environment;
• Azure Data Factory, Azure Storage (Blob or Data Lake), Databricks, Azure Functions, SQL Azure DB, SQL Azure DW, Synapse, Azure DevOps -CI/CD, GIT, JIRA etc.,
• Knowledge in python
• Agile Methodology
• English: C2 Proficient
• Hands-on business intelligence development or data engineering experience
• Extensive ETL experience
• Good exposure to data warehouse design and data lake concepts and practices
• Exposure to working in a Microsoft Azure Data Platform environment
• Azure Data Factory, Azure Storage (Blob or Data Lake), Databricks, Azure Functions, SQL Azure DB, SQL Azure DW, Synapse, Azure DevOps -CI/CD, GIT, JIRA etc., Knowledge in python