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- Tasks: Join a leading insurance company to optimise data models and architecture.
- Company: Work with a top-tier insurance firm focused on innovative data solutions.
- Benefits: Enjoy hybrid work flexibility and the chance to shape data strategies.
- Why this job: Be a key player in driving data consistency and efficiency across the business.
- Qualifications: Extensive data modelling experience and knowledge of AWS required.
- Other info: This is a 6-month contract role with an urgent start date.
The predicted salary is between 60000 - 84000 £ per year.
Job Type: Contract/Temporary
Location: London (Hybrid - 2 days per week in London)
Length: 6 months
Urgent requirement for a Data Modeller / Architect to join a leading insurance company. The role will focus on reviewing the current state of our data mart models & architecture, defining standards & guardrails then working with federated areas to ensure adherence to these. The resource will spearhead the community of data modellers across the business to drive consistency in our modelling strategy, reducing inefficiencies and enabling simpler structures to drive quicker time to insights across the business.
Key Responsibilities:
- Review existing domain data mart models/architecture to ensure that they meet the needs of our data strategy and are optimised to support our key analytical use cases.
- Design and develop remediated designs/models and work with engineering and analytical stakeholders across the different domains to create backlogs for model standardisation and improvements.
- Ensure storage and consumption approaches/designs deliver maximum efficiency, with a focus on balancing storage and compute costs optimally.
- Produce and maintain modelling and design guardrails, standards and processes and integrate these with wider data management and engineering governance.
Key Skills:
- Data design patterns and optimisation across disparate mediums within a Cloud-based environment (preferably AWS) such as data warehouses, redshift, and lake house architecture.
- A strategic thinker who can define modelling patterns for various layers of a data environment balancing storage vs. compute costs, optimised for as broad a set of use cases as possible.
- Extensive data modelling experience, from conceptual to physical.
- Expertise in different modelling methodologies such as 3NF, Dimensional, Data Vault.
- Expertise in building cloud data warehouses using Kimball, preferably using AWS Redshift.
- Knowledge/experience of building queries and MI outcomes utilising data visualisation technologies (e.g., Tableau).
- Qualifications in RDBMS design and/or administration and in AWS architecture (at least one of these).
- Awareness of data governance and data ethics in the production of automated modelling.
- Proven track record of delivery of modelling designs/approaches in large scale data environments.
- Evidence of broad stakeholder management from senior business level down to analyst.
- Experience in, or extensive exposure to MI/BI use cases, data exploration and analysis.
- Experience within predictive modelling/Data Science would be an advantage.
- Experience in defining and delivering data monitoring across a large platform as well as establishing governance forums, processes and guardrails to ensure compliance with standards.
Data Modeller / Architect - Outside IR35 employer: Lorien
Contact Detail:
Lorien Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Modeller / Architect - Outside IR35
✨Tip Number 1
Network with professionals in the insurance and data modelling sectors. Attend industry meetups or webinars to connect with potential colleagues and learn about their experiences. This can give you insights into the company culture and expectations.
✨Tip Number 2
Familiarise yourself with the latest trends in cloud data architecture, especially AWS. Being able to discuss recent developments or case studies during your conversations can demonstrate your passion and knowledge in the field.
✨Tip Number 3
Prepare to discuss specific examples of your previous work in data modelling. Highlight how you've optimised data structures or improved efficiency in past roles, as this will showcase your practical experience and problem-solving skills.
✨Tip Number 4
Engage with the company's online presence. Follow them on LinkedIn, comment on their posts, and share relevant content. This not only shows your interest but also helps you stay updated on their latest projects and initiatives.
We think you need these skills to ace Data Modeller / Architect - Outside IR35
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data modelling and architecture. Focus on your expertise with cloud environments, particularly AWS, and any specific methodologies you've used, such as 3NF or Data Vault.
Craft a Compelling Cover Letter: In your cover letter, emphasise your strategic thinking and ability to define modelling patterns. Mention your experience in stakeholder management and how you can contribute to the company's data strategy.
Showcase Relevant Projects: Include examples of past projects where you've successfully designed and implemented data models. Highlight any experience with data visualisation technologies like Tableau and your role in optimising storage and compute costs.
Highlight Qualifications: Clearly state your qualifications in RDBMS design and AWS architecture. If you have any certifications or training related to data governance or ethics, be sure to mention those as well.
How to prepare for a job interview at Lorien
✨Showcase Your Data Modelling Expertise
Be prepared to discuss your extensive experience in data modelling, including specific methodologies like 3NF, Dimensional, and Data Vault. Highlight any projects where you've successfully implemented these techniques, especially in cloud environments like AWS.
✨Demonstrate Strategic Thinking
Since the role requires a strategic thinker, come equipped with examples of how you've defined modelling patterns that balance storage and compute costs. Discuss how your decisions have optimised data environments for various use cases.
✨Engage with Stakeholders
Prepare to talk about your experience in managing stakeholders at different levels. Share instances where you've collaborated with engineering and analytical teams to drive consistency in modelling strategies and improve efficiencies.
✨Understand Data Governance
Familiarise yourself with data governance and ethics, as these are crucial for the role. Be ready to discuss how you've established governance processes and guardrails in previous positions to ensure compliance with standards.
