Data Architect

Instem
Stafford
3 weeks ago
Applications closed

Related Jobs

View all jobs

Data Architect

Data Architect

Data Architect

Data Architect

Data Architect

Data Architect

1 week ago Be among the first 25 applicants


Get AI-powered advice on this job and more exclusive features.


Location: Stone, Staffordshire Hybrid working, 2 days a week in our Stone Office


Status: Permanent, Full Time


Package: Competitive Salary, Flexible Working, Development & Opportunity (Personal & Technical), Private Medical (Optical & Dental options), Matching Contributory Pension, 25 Days Leave + Public Holidays + Buy and Sell Scheme, Life Insurance, Referral Scheme, Employee Assistance Program, Benefits Hub.


Who’s Instem? Well, we’re a global provider of bespoke industry-leading software solutions and services, which facilitate the pre‑clinical, and clinical phases of the drug discovery process. We have over fifteen products in our portfolio, used by over 700 pharmaceutical clients (including all the top 20!)


What’s the culture/environment like? For a global business of over 400 staff, we very much have a family feel. You’ll be part of a friendly, communal, solution based, flexible environment, where you’ll feel empowered, valued and accountable. We’ll invest in you as a person and encourage you to take part in companywide workshops for wellbeing, mental health, critical conversations, and strengths.


Why are we hiring a Data Architect? We are seeking an experienced and hands‑on Data Architect to help shape the future of our data landscape – across both our software products and internal enterprise systems.


What are you responsible for?

  • Data architecture and modelling
  • Analyse and document the current data model across products and platforms
  • Define a modern, future‑ready data architecture that supports scalability, interoperability, and reuse across customer environments (including multi‑tenant data models)
  • Develop and maintain canonical and conceptual data models, supporting common understanding across teams
  • Work with product teams to ensure data models support both functional needs and data governance principles
  • Data management and best practice
  • Establish and champion data management best practices, covering data quality, naming conventions, lineage, and lifecycle management
  • Promote standards for metadata management, master data management (MDM), and reference data
  • Define and advocate for data governance frameworks aligned to business priorities and regulatory requirements
  • Help teams implement best practices through hands‑on demonstration, prototype data models, and reusable design patterns
  • Collaboration and enablement
  • Work closely with architects, product managers, and engineering leads to embed sound data design principles into products and services
  • Partner with business stakeholders and analysts to align data definitions, semantics, and business rules
  • Mentor and upskill developers and analysts in data architecture, modelling tools, and practices
  • Support architecture governance through participation in the Architecture Review Board and related forums

Skills, Knowledge, Experience

  • Proven experience as a Data Architect, Senior Data Modeller, or Data Engineering Lead in a complex software or SaaS environment.
  • Deep understanding of conceptual, logical, and physical data modelling
  • Hands‑on experience with relational and NoSQL databases technologies (e.g. SQL Server, PostgreSQL, MongoDB)
  • Strong grasp of multi‑tenant data architectures, data isolation, and schema design for configurable solutions
  • Experience designing and maintaining enterprise or product‑level data models
  • Working knowledge of data integration patterns, APIs, and ETL/ELT processes
  • Familiarity with data governance frameworks (e.g. DAMA‑DMBOK) and metadata management concepts
  • Strong communication and collaboration skills – able to bridge the gap between technical teams and business stakeholders

An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.


Instem stores and processes data using an Applicant Tracking System (ATS). For more information regarding our privacy policy use the following link: https://www.instem.com/privacy/


Seniority level

Mid‑Senior level


Employment type

Full‑time


Job function

Engineering and Information Technology


Industries

Research Services


#J-18808-Ljbffr

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.

Careers Jobs

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

Jobs

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Education Jobs

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.