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Senior Data Engineer - DV Cleared

Fortice
City of London
2 weeks ago
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As a Data Specialist at this tech scaleup in London, you will analyse, collect, sort, and create data solutions that integrate across multiple products. You will steer decisions regarding data and build the models that power their products.


You will take client insights and requirements and make them a reality, by developing datasets and operational models to drive innovation into the product development process. You will interpret your client’s objectives, desires, and preferences to help the wider technical team understand the opportunities and apply data engineering responsibilities consistently.


You will be working on an interesting range of projects that deliver to National Security customers and as such, you will have to hold the highest level of UK Security Vetting (DV), upon application.


Key Responsibilities:


You will blend Data Engineering and Data Science, and will have experience that might cover a number of the tasks listed below:


Data Engineering tasks

  • Manage the implementation and development of integrations between the data warehouse and other systems.
  • Create deployable data pipelines that are tested and robust using a variety of technologies and techniques depending on the available technologies (Nifi, Spark)
  • Build analytics tools that utilise the data pipeline to provide actionable insights into client requirements, operational efficiency, and other key business performance metrics.
  • Complete onsite client visits and provide excellent customer support service.
  • Problem-solve in a pragmatic way, showing direction and technical support for clients whilst being agile in the approach and methodology.


Data Scientist tasks

  • Build robust, containerised data science capabilities which are scalable across projects and products (Docker, Kubernetes)
  • Collaborate with technical teams to write production-ready code, ensuring ML and AI models are deployable for your clients and projects.
  • Collaborate with software engineers to design and deploy machine learning services that are accessible via APIs for use in GUIs or direct access.
  • Research, analyse and apply data sets using a variety of statistical and machine learning techniques.
  • Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project.
  • Review the execution of software solutions and how these perform for the business and your clients, establishing key findings and commercially minded resolutions.
  • Work with the Business Development team to create proposals and bids for new work.


Benefits:


  • £65,000 - £85,000 base + package
  • The business offers genuine autonomy and flexibility.
  • You'd work hybrid working (to client site, as there is no office)
  • You will manage your hours, core hours are 10am - 2pm – the other hours you work are up to you.
  • 27 days holiday plus bank holidays and a generous Maternity/Paternity policy.


Process:


  • On applying, you can expect a two-stage process which is typically completed in two weeks. You will first have a virtual meeting with the Head of Engineering. This will be a refreshingly open discussion around the company and their journey so far as well as a chance to speak more openly about you and what you enjoy doing.
  • Following this, a final stage 60-minute video call or face-to-face will be arranged where you can expect to delve further into your background and technical skill-set as well as scoping out what a potential role would look like.


Equality and Inclusion:


Fortice are committed to creating diverse and inclusive teams. Fortice strongly encourages people of all identities and communities to apply to the roles we advertise, it may well be that you could be more suited to a different opportunity.


Regardless of background, race, religious beliefs or sexual orientation, fortice exists to enable good people, to do better work with greater outcomes.

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