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Data Engineer

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Media platform company is currently looking for a Data engineer to join their growing team. Are you hands on experience with Big Data Technologies?

Then this is the right opportunity for you!

Main Responsibilities:

  • Creating and maintaining the data pipeline

  • Building the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources.

  • Designing, coordinating and executing scalable data processing and analytics solutions, including technical feasibility for Big Data storage, processing and consumption.

  • Identifying, designing, and implementing internal process improvements.

  • Ensuring plan execution, document and share technical best practices / insights with stakeholders to assist with data-related technical issues and support their data infrastructure needs.

  • Building analytics tools that utilize the data pipeline to provide actionable insights for data scientist team members.

Skills Required:

  • Minimum 3 years Experience in a similar Data Engineering role, who has attained a Graduate degree or above in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.

  • Experience in designing big data real-time processing solutions

  • Building and implementing Big Data solutions using Microsoft Data Platform and Azure Data Services; including Data Factory, Data Warehouse, Data Lake, Data Lake Analytics, Data Bricks and U-SQL

  • The right candidate must also be able to support and work with cross-functional teams in a dynamic environment in an AGILE development environment.

  • Desired certifications preferably in one or both or comparable:

    •  Microsoft Azure Designing and Implementing Big Data Analytics Solutions (70-475)

    • Microsoft Azure Designing and Implementing Cloud Data Platform Solutions (70-473)

  • Experience of hybrid and/or cloud architectures that utilise Azure

  • Experience of advanced data analytics and insights techniques such as predictive, segmentation, recommendation and sentiment analytics, machine learning techniques and leveraging structured and unstructured data.

  • Expert knowledge and experience in some of the following;

    • Hadoop, Spark, Storm, Hive

    • NoSQL, CosmosDb, MongoDb

    • R Studio, PowerBI, Visual Studio, TFS

    • C#, R, Python, SQL, MDX, JSON, XML, .NET, C++, T-SQL, Java, JSON, Scala


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