What is the role of an Azure Data Engineer?
In your role as an Azure Data Engineer, you will be responsible for expanding and optimising data and pipeline architectures, and for optimising data collection and flow across functional teams. Your responsibilities include assisting software developers, database architects, data analysts, and data scientists with data initiatives and ensuring a consistent data delivery architecture is put in place throughout ongoing projects.
Responsibilities
Assure that data is cleansed, mapped, transformed, and otherwise optimised for storage and use according to business and technical requirements
Develop and maintain innovative Azure solutions
Solution design using Microsoft Azure services and other tools
The ability to automate tasks and deploy production standard code (with unit testing, continuous integration, versioning etc.)
Load transformed data into storage and reporting structures in destinations including data warehouse, high speed indexes, real-time reporting systems and analytics applications
Build data pipelines to collectively bring together data
Other responsibilities include extracting data, troubleshooting and maintaining the data warehouse
Tech Stack
Python
SQL and NoSQL databases
Scala
Spark-SQL
Experience with Azure: ADLS, Databricks, Stream Analytics, SQL DW, COSMOS DB, Analysis Services, Azure Functions, Serverless Architecture, ARM Templates
Types of Azure Data Engineer
SQL Developer
Data Engineer
Data Scientist
Artificial Intelligence (AI) Engineer
Qualifications
Previous experience as an Azure Data Engineer or similar role
Experience building and optimising 'big data' data pipelines, architectures, and data sets
Strong analytic skills related to working with unstructured datasets
The ability to design and implement well written code
Ability to work to tight deadlines
Ability to test the data from source to the presentation layer
Ability to support/troubleshoot data pipelines
Confident and concise communication skills, with the ability to drive alignment, collaboration, and efficiency within teams