Job Title- Data Engineer
Location- London/ Remote
Salary- £55,000- £60,000
You will be working for a leading financial service consultancy, working as a Data engineer on client projects. It will be your responsibility to ensure that the design of the data solution and the architecture work together efficiently. P Proactively identifying potential issues. Owning the overall design and implementation of the data solution.
- Discretionary share options & profit sharing scheme
- Private medical insurance with Vitality
- Long term disability & death in service insurance
- Pension contribution of 6% with option to increase by a further 3%
- 25 days holiday / year increasing by 1 day per year of service to a maximum of 30 days
Role & Responsibilities
- You will be working with the customer business users to ensure that the design of the solution accurately supports the customer's business requirements
- Understanding and leveraging expert knowledge of Data Engineering and DataOps approaches and products, 3rd party technology and technology trends
- As required, adopting the role of a Data Architect to ensure that the data architecture is compatible with the overall system architecture and meets non-functional requirements
- Identifying project risks / escalating issues and feeding back information to Managing Consultants, Project Managers, and/or Senior Management
- Providing input for work breakdown and estimation.
- Under the direction of a Project/Program Manager plan, run, and manage meetings with internal and external clients and leading quality assurance reviews
- Sharing best practice experience, advice and techniques
Skills & Qualifications
- Minimum 5+ years of data engineering.
- Ability to apply industry standard development approaches specifically agile continuous integration, continuous delivery through DataOps.
- Detailed Design, Coding, and Testing (Unit/CIT) of data pipelines within an existing product framework.
- Support for SIT and system test including building test data setsStrong written and verbal English language communication skills
- Database engineering
- SPARK ETL, and pipelines engineering
- SQL knowledge
- Python data skills
- Knowledge about Excel and end user data tools
- Knowledge of reporting systems and patterns
- Azure knowledge
- JSON and Tabular data formats
- Docker / Kubernetes
- Ability to use Git