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Data Engineer

The role is with a Banking company that have over 1.7m customers andaim to help people who are excluded by mainstream banks and allow them to take control of their financial situation. Whether they're new to credit or need a hand rebuilding their credit file to manage life better, they make sure their services are straightforward and suitable for their customers to succeed.

You and your team

Data is such an important focus at the company where they use it every day to better utilise data as whole improving their customer's outcomes and satisfaction! At the core of the company's strategic data initiative is to establish a strong Data Platform that mees the data provisioning needs of Consumers. They are adopting a Cloud-first approach to deliver an advantage to how we look at Data. Working closely with all areas of the Business as well as technology teams you will be involved in the migration to a cloud-based architecture that can scale performance on demand.

In your day to day role you will:

  • Translate raw data into usable datasets to support business requirements.
  • Deliver robust, high-performing and scalable solutions for loading, transforming and processing company data.
  • Develop adhering to the current development best practices whilst contributing to the continual improvement of these practices.
  • Maintain formal data and metadata structures (lineage) to support integrity and searchability of information via a data dictionary.
  • Working collaboratively with:
    • Data engineers for guidance and review of tasks
    • Our Data Architect to define and build data marts
    • Our Data Platform team to ensure high level of performance and provide support for delivered solutions

What you'll bring to the team

As a Data Engineer you will be looking at the the company can transform their data sets while staying ahead of the curve with the technology stack they are using. As a team, Data work on all areas of the business and is crucial to how we move forward not only within technology but in the commercial world.

  • Experience of end to end implementation of Data Engineering and Analytics over a Cloud Infrastructure - Preferably with Azure
  • Technical versatility with Azure offerings including Databricks or Spark, Azure Data Factory, Azure Data Lake, DevOps
  • Strong knowledge of Big Data technologies such as Nifi, Hive, Spark, Kafka HBase
  • Excellent troubleshooting, performance tuning and security awareness