Azure Data Engineer
This role is for a Data Engineer Microsoft BI (Azure) to join our Analytics and Artificial Intelligence team.
Analytics and Artificial Intelligence team create state of art machine learning models to help business deliver high value, smart and market differentiating engineering products and services. The focus of our team is innovative algorithms and models that make intelligent, automated, decisions in real time to make engineering process better, faster and accurate. To achieve that we collaborate with the engineering, sales, commercial and technology teams.
- Responsible for implementing robust data pipeline using Microsoft Stack
- Responsible for creating reusable and scalable data pipelines
- Responsible for development and deployment of new data platforms
- Responsible for using Azure BI services for development of Big Data Platforms
- Responsible for creating reusable components for rapid development of data platform
- Responsible for deploying AI algorithms in to the data platform.
- Work closely with the Product Owners and Architects to develop Azure Data Platforms including Machine Learning.
- Work with the leadership to set the standards for software engineering practices within the machine learning engineering team and support across other disciplines
- Play an active role in team meetings and workshops with clients.
- Choose and use the right analytical libraries, programming languages, and frameworks for each task
- Produce high-quality code that allows us to put solutions into production
- Refactor code into reusable libraries, APIs, and tools.
- Help us to shape the next generation of our products.
- 3-5 years of experience in Data Warehousing with Big Data or Cloud
- Graduate degree educated in computer science or a relevant subject
- Good software engineering principals
- Strong SQL Server 2012 and above with MSBI (SSIS, SSRS, SSAS)
- Good understanding of OLAP data models design
- Experience in working on Azure Services like Azure Data Factory
- Knowledge of Power shell
- Experience of working in Agile delivery
- Knowledge of Big Data technologies, such as Spark, Hadoop/MapReduce is desirable but not essential
- Knowledge of Azure services like HD Insight, Azure DataBricks etc.
- Working knowledge of the pros, cons and usages of various ML/DL applications (such as Keras, Tensorflow, Python scikit learn and R)
- Contribution to industry/open source communities.
- Knowledge and practical experience of cloud based platforms and their ML/DL offerings (such as Google GCP, AWS, and Azure) would be advantageous
- Understanding of infrastructure (including hosting, container based deployments and storage architectures) would be advantageous