I'm currently working with an online education business who are looking for a Senior Data Engineer to join the business and work directly alongside the CTO. They're open to remote working but are hoping for someone to head in one day a week to work alongside the team. They provide a fantastic array of courses and subjects areas for people to progress their education and gain further certifications. They are investing very heavily in their technology division currently, with this Senior Data Engineer role being a great opportunity to further the technology arm of their business.
Key skills & Requirements for a Senior Data Engineer :
- Working alongside the CTO and enterprise architect to develop a robust but scalable Data Architecture and roadmap to support organisational growth.
- Work with key stakeholders to ensure robust data governance policies and procedures are in place for the ownership, maintenance and verification of all corporate data.
- Develop and embed a framework for improving data quality and standards.
- Curiosity and drive to understand business processes and the data they generate in addition to the opportunities to structure and use this data to drive business value.
- Lead contributor on aspects of data security, able to lead and deliver architecture best practice across their data services portfolio.
- Develop and own the application interface tier between several critical business systems and data sources using ETL tools (e.g. Azure Data Factory) to improve data quality and aid the digital transformation.
- Responsible for the maintenance of database architecture and work alongside other Data engineers and BI staff to develop Business Intelligence and reporting solutions, as well as troubleshooting data related & reporting issues.
- Ensuring the data models developed meet the appropriate standards and principles.
- Knowledge of the Enterprise Architecture Frameworks (TOGAF) and application thereof.
- Key Data Architecture skills include but are not limited to: Data Analysis, Data Profiling, Data-modelling, Data Warehouse Design, Data Lakes, Big Data Design, Data Lifecycle management, Master Data Management & implementation patterns, Data Integration patterns and methods.
- Abreast of the latest industry developments across data, including machine learning and modern algorithmic techniques at scale.
- Strong communication and influencing skills used to drive the implementation of data design best practice.
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