Lead Data Architect

Hippo
Bristol
1 month ago
Create job alert
About The Role

Hippo is recruiting for a Lead Data Architect to join our Hippo Herd. Our Lead Data Architect will work in multi-disciplinary teams that build, support & maintain user-centred data solutions that offer real value and work for everyone.

As a Lead Data Architect, you will be responsible for contributing to and implementing data governance standards that ensure that our clients’ data is high quality and fit for purpose. You will design and implement solutions on leading edge data cloud platforms that adhere to high standards of security, privacy and accessibility that unlock business insights and opportunities for data-driven business decisions.

Please note, we are looking for candidates who are looking for growth at this level (Lead), therefore the advertised salary band is the lower end of our full banding for this level of position, allowing for progression in the role.

Your Role In a Nutshell
  • Define a data architecture that satisfies the data requirements of all stakeholders in an organisation and adheres to the enterprise wide data and technical strategy
  • Build and maintain appropriate Enterprise Architecture artefacts including Entity Relationship Models, Data Dictionary, ETL/ELT definitions and Data Pipeline/Lineage Models
  • Be accountable to the client for the rationale of the architecture and detailed solution and be able to evidence that a thorough change approval process has been followed
  • Define the methods and standards of governance to ensure ongoing integrity of the architecture design artefacts
  • Define standards for data modelling to ensure consistency within the solution and across the enterprise. Be a vocal and assertive advocate of data warehousing modelling techniques such as Kimball
  • Be versatile in working within a delivery team to:
    • Analyse candidate data sources for content, timeliness and integrity
    • Evaluate APIs by analysing documentation and sample responses
    • Reverse-engineer data models from a live system
    • Create Agile stories for the implementation of the solution and support the engineering team throughout development
    • Support third party suppliers in developing specifications that ensure compatibility between client and supplier systems
    • Support integration and reconciliation testing
    • Visualise insights using industry standard reporting tools
About The Candidate
  • Proven experience in defining data architectures to satisfy multiple stakeholders with varying data proficiency
  • Thorough understanding of data lake and data warehousing principles and full project involvement in one or more major technology platforms, e.g. Snowflake, Databricks, etc.
  • Proven experience with one or more Cloud Services provider, e.g. AWS, Azure or Google Cloud Platform
  • Good understanding of role-based access control, its importance in data privacy and methods of implementation
  • Excellent data modelling skills in designing data warehouses and datamarts
  • Experience of migrating data from legacy on-prem systems to cloud architectures
  • Knowledge of OLTP and OLAP principles and evidence of building such solutions
  • Evidence of building and managing the evolution of entity relationship models, data dictionaries and ELT/ETL models
  • Ability to visualise outputs using leading reporting tools such as Power BI (with custom DAX) and/or Tableau
  • High proficiency in SQL. Knowledge of SQL Server, SSMS, SSIS and SSRS a bonus
  • Ability to evaluate APIs using tools such as Postman
  • Consultancy experience is highly desirable
  • Experience designing and implementing data pipelines is highly desirable
About The Company

As well as a competitive salary which we’re transparent about from the outset, you can also expect a range of benefits:

  • Contributory pension scheme (Hippo 6% with employee contributions of 2%)
  • 25 days holiday plus UK public holidays
  • Perkbox access for a wide range of discounts
  • Critical illness cover
  • Life assurance and death in service cover
  • Volunteer days
  • Cycle-to-work scheme for the avid cyclists
  • Salary sacrifice electric vehicles scheme
  • Season ticket loans
  • Financial and general wellbeing sessions
  • Flexible benefits scheme with options of:
    • private health cover
    • private dental cover
    • additional company pension contributions
    • additional holidays (up to an extra 2 days)
    • wellbeing contribution
    • charity contributions
    • tree planting
Diversity, Inclusion and Belonging

Hippo is dedicated to creating a diverse, equitable and inclusive workplace that works for everyone. We encourage applications from underrepresented groups and are committed to providing an inclusive and accessible recruitment process. We are a Disability Confident Employer, Mindful Employer, Endometriosis Friendly Employer and a member of the Armed Forces Covenant. We strive to remove barriers and offer reasonable adjustments.

Hi, we’re Hippo. We design with empathy and build for impact. We are a digital services partner invested in helping our clients thrive as modern organisations. Our delivery methodology is agile, from concept to reality, supporting innovation and continuous improvement to achieve outcomes. We believe technology should serve humanity and take a human-centred approach to our work.

Hippo locations: We are headquartered in Leeds with offices across the UK in Glasgow, Manchester, Birmingham, London and Bristol. You need to be located within reasonable travelling distance from one of our offices. Client work may require on-site presence and travel. Relocation support up to £8k is available.

Seniority level: Mid-Senior level

Employment type: Full-time

Job function: Consulting and Information Technology

Industries: Professional Services


#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Data Architect

Lead Data Architect

Lead Data Architect

Lead Data Architect

Lead Data Architect

Lead Data Architect

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 Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

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

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

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

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.