Senior Data Engineer - Data Science Team

  • Location


  • Ref


  • Hours


  • Closing date

    18 Jan 2019


About the role

The Data Science team is excited to be recruiting an exceptional Data Engineer into their growing and hugely successful team which is made up of talented and diverse individuals including PhD graduates and Data Scientists. The team is driving the implementation of machine learning across the entire organisation with a focus on the delivery and realisation of benefits.

The team helps LV build data pipelines and machine learning solutions across the business. The team operate as a consultancy within the business. They are approached by different parts of the business who they then work closely with to create an end to end solution. They are involved in all aspects of the project from data collection, to model building to model deployment.

This is an opportunity for someone with curiosity, to look beyond raw data and tell the story behind it. A chance to develop and operationalize analytics solutions, to answer key business questions and improve business processes by leveraging machine learning. The possibilities are huge. We are looking for an experienced Data Engineer who is able to lead the end to end process of machine learning model building and deployment.

About you

We don't expect you to know everything from day one, but for we do require a certain amount of experience in producing and deploying models in business scenarios:

  • Significant knowledge and capability ML model operationalisation technologies such as:
    • Kubernetes
    • Docker
    • Python (incl. common ML packages & REST web services)
  • Experience of data storage, manipulation and extraction tools including relational databases, unstructured / NoSQL data stores, ETL, query processing and other data pipeline processing infrastructure
  • Knowledge and capability in DB / data storage tools / processes e.g. Oracle, SQL Server
  • Familiarity with monitoring, backup and DR of data systems
  • Knowledge and capability in Microsoft Azure data & analytics PaaS technologies including some of the below:
    • Azure Data Factory
    • Azure Data Lake Store
    • SQL Data Warehouse / Database PaaS
    • Azure HDInsight / Hadoop
    • Azure DataBricks
    • Azure Machine Learning Services
    • PowerShell
  • Knowledge of and capability in R
  • Knowledge of alternative cloud platforms such as AWS & Google Cloud
  • Knowledge of Microsoft Cognitive Services
  • Proven experience of leading technical projects around large datasets
  • Ideally you will have a PhD or a masters plus experience in a highly numerate degree / career
  • Excellent stakeholder management skills, including communication, management of expectation, recommendations, quality of outputs, and working accurately to tight deadlines
  • Experience to build and maintain relationships both externally and with customers throughout the company.
  • Quick to learn, ability to prioritise activities and responsive to the needs of the business.
  • Proven experience in  mentoring or managing technical teams in the use of technical software
  • Ability to convey technical concepts to a non-technical audience


Your role will vary day to day, but here is a bit of what you can expect:

  • To liaise with business SMEs to achieve a common understanding of the business challenge, their needs, data requirements and expected output
  • To be responsible for the operationalisation of ML models, including establishing repeatable and maintainable best practices and patterns for development, testing and deployment.
  • To be responsible for the development and maintenance of automated, repeatable processes for integrating data and providing it to analytics users in an appropriate format. To include documentation, testing aligned with agreed processes and standards.


  • To work closely within a cross functional team to scope, develop, articulate progress and results including business case to progress further. (End to end - Technical to business use)
  • Work with architects / SME to develop processes for productionising use cases
  • Become one of a group of experts who can coach business SMEs as part of handover to ensure the capability continues to grow across the group
  • Working on all aspects of the project as needed by the overall team
  • Help formulate a longer term operating and support model for analytics.
  • Actively championing analytics across all areas and levels of the business
  • Working with architects and data scientists, provide technical input into matching the best technology to the use case and develop an ongoing process
  • To be responsible for maintaining standards around the use and access to data, ensuring adherence to internal and external regulatory factors, standards, policies and procedures.
  • Evaluates and provides feedback on future technologies and new releases / upgrades

Rewards and benefits

This role is a Band C in the LV= Structure. To find out more about our bands, click to view our FAQ page here. We want you to love what you do that’s why we’ve put together a benefits package that recognises and rewards a job well done.  

We’ll give you:

  • 30 days' holiday, with the option to buy up to 2 additional days
  • a competitive pension for which LV= will pay twice the amount you pay, up to 14% (please click here to read more about it)
  • an annual bonus scheme based on company and personal performance
  • Single cover private medical insurance which you can upgrade to family cover
  • a flexible benefits package (e.g. discounted retail vouchers, great value dental insurance, childcare vouchers)
  • a generous 25% discount off our general insurance products including home, pet and travel.  Up to 50% discount on your car insurance and up to 20% discount from our life products.

To find out more about our benefits and rewards, please click here.

Here at LV= we always love to hear from great people, so don’t forget to follow us on InstagramTwitterLinkedIn and become a fan on Facebook. We’re also proud to say we’re an equal opportunities employer.  Why not follow us on Glassdoor and take the opportunity to see real reviews of what it’s like to work here. 

You may find making an application much easier from a desktop computer. So why not forward yourself a link to this vacancy to pick up and apply on a desktop or laptop later. Alternatively you can send the link to someone you think would be suitable for the role.

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