Data Modeler

Birmingham
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer - DataOps

Senior Data Scientist

Senior Climate Data Scientist

Pricing Actuary / Data Scientist F/M

Data Engineer - AI Analytics and EdTech Developments

Data Scientist (Government)

Data Modeller
Location: Birmingham, UK (5 days a week in the office)

Our client is seeking an Experienced Data Modeller to join their team, playing a key role in designing and maintaining data models that support audit and risk assessment processes. This role will involve close collaboration with auditors, business stakeholders, and IT teams to ensure data integrity and alignment with business objectives.

Key Responsibilities:

Develop and maintain logical and physical data models to support audit and risk functions.
Build and implement reporting and analytics solutions using tools such as Tableau, Power BI, Looker, or Qlik.
Design interactive dashboards that provide clear insights into audit outcomes and risk assessments.
Ensure data quality, validation, and compliance with regulatory standards.
Maintain data dictionaries, metadata, and schema documentation.
Optimise data pipelines and warehousing solutions for both structured and unstructured data.
Use SQL and data modelling tools (e.g., Erwin, Visio) to define and implement database solutions.
Improve dashboard performance and user experience through best practices in data visualisation.

What Our Client is Looking For:

A degree in Data Science, Computer Science, Information Systems, or a related field.
At least 7 years of experience in data modelling, database design, and data architecture.
Proficiency in data modelling tools such as Erwin, ER Studio, Lucidchart, or PowerDesigner.
Strong SQL skills and experience with both relational and NoSQL databases (e.g., Oracle, SQL Server, PostgreSQL, MongoDB).
Hands-on experience with reporting and analytics tools like Tableau, Power BI, Looker, or Qlik.
A solid understanding of dashboard design and data visualisation principles.
Knowledge of audit processes, risk management, and compliance frameworks (desirable).
Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies (Hadoop, Snowflake, Databricks) is a plus.
Strong analytical, problem-solving, and communication skills.
The ability to work in a fast-paced, dynamic environment and manage multiple priorities.

Bonus Skills:

Experience in financial services, banking, or regulatory environments.
Knowledge of data governance and data lineage tools.This is an exciting opportunity to work with a forward-thinking organisation that values data-driven insights in audit and risk management. If you have the skills and experience required, we'd love to hear from you.

To apply or learn more, please get in touch.

Randstad Technologies Ltd is a leading specialist recruitment business for the IT & Engineering industries. Please note that due to a high level of applications, we can only respond to applicants whose skills & qualifications are suitable for this position. No terminology in this advert is intended to discriminate against any of the protected characteristics that fall under the Equality Act 2010. For the purposes of the Conduct Regulations 2003, when advertising permanent vacancies we are acting as an Employment Agency, and when advertising temporary/contract vacancies we are acting as an Employment Business

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.