Principal Consultant - Data Engineering Lead

Intuita
Newbury
1 day ago
Create job alert

Salary: £70,000 - up to £95,000 (dependant on experience)


Contracting and Permanent hires considered


🏢 Location: ALL locations considered: We have offices in Liverpool or Newbury office UK for Hybrid working and Sibenik (Croatia)


Let us introduce ourselves


We’re Intuita, a new kind of data partner.


We’re a collective of data-driven people ready to cut through complexity to solve business problems in a human-centric and sustainable way. We provide pragmatic end-to-end services, products and technologies combined with straight-talking strategic direction to unlock the true value of data and drive transformational change.


Established in 2011 as a different player to the corporate data world, our ethos is to do the right thing, even if it’s not the easy thing; to build partnerships and relationships based on honesty and transparency; and to prioritise specialist skills and quality above all else. Now as part of the wider FSP Consulting group, we continue with our ambitious growth plans.


📝 The role

We are looking for a Principal Data Engineer on a permanent contract basis, to join our talented Data Engineering team. In this key role, you will work closely with our Engineering Director to support the development of our high-performing team, applying your extensive engineering expertise to drive business growth and lead consultancy-driven projects.
This position calls for a leader with a strong combination of hands-on technical excellence and exceptional leadership skills to steer our teams toward achieving both quality and strategic objectives. Ideally you will have managed a team of engineers with proven success.


Key Responsibilities:

  • Technical Leadership & Mentorship: Guide and mentor a team of engineers, providing technical direction, support and develop their skills to ensure the highest quality outcomes for our clients.
  • Technical Project Ownership: Responsible for the technical direction and execution against critical business transformations, ensuring both sustainability and quality. Working closely with Business Analysts to ensure the technical solution meets 100% of the business needs.
  • Client Engagement: Act as the technical liaison between the engineering teams and clients, ensuring client satisfaction through well thought out solutions with longevity in mind.
  • Quality Assurance & Best Practice: Establish and enforce data engineering standards, best practice, reusable frameworks. Quality assurance management through data engineering pipelines, ensuring both quality and performance of solutions.
  • Continuous Improvement: Stay up to date with the latest developments in technology changes within respective field/and or specialism, and proactively engage with wider engineering team on learning opportunities.
  • On-Site Engagement: Periodically visit client sites to foster and strengthen relationships, ensuring our commitment to partnership and collaborative success is clearly demonstrated.

Being a consultant at Intuita means something a little different to being a consultant elsewhere, we like to hire driven characters who share our passion and approach, bringing their style and flare. We see ourselves as trusted partners to our clients and believe in transparency, quality and integrity above all else, always pushing the boundaries to deliver the best outcomes for our clients. We also really value collaboration and teamwork, making sure we work together to solve problems and share learnings as a team.


As a Lead role within our Data Engineering discipline, you’ll share these values but also bring your own personality and approach to the role. We’re looking for someone with the following experience and qualities, but if you don’t fit these exactly and are interested in working for us, get in touch anyway – we hire people, not job specs.



  • Extensive hands‑on experience in a business transformation setting, either at enterprise level or in large‑scale delivery
  • Proven success as a Team Leader, managing a team of Data Engineers on various projects
  • Proven experience in data engineering and architecture, with a focus on developing scalable cloud solutions in Azure, GCP or AWS.
  • Data Modelling using Kimball, 3NF or Dimensional methodologies
  • Analytics Engineering lean, with experience within BigQuery (GCP) with data modelling in DBT and mobile/telecoms industry experience would be beneficial, with deep DBT experience being highly beneficial
  • Depth of knowledge and understanding across core orchestration tools and CI/CD pipelines to enhance development efficiency and deployment effectiveness, including Azure DevOps or GitHub
  • Considerable experience designing and building operationally efficient pipelines, utilising core Cloud components, such as Azure Data Factory, Big Query, AirFlow, Google Cloud Composer and Pyspark etc
  • Proven experience in modelling data through a medallion‑based architecture, with curated dimensional models in the gold layer built for analytical use
  • Strong understanding and or use of unity catalog alongside core databricks functionality to drive metadata management
  • Strong understanding of cloud economics, including cost management strategies and optimising solutions for customer needs
  • Experience with infrastructure as code, proficiency using tools such as Terraform to automate and manage cloud infrastructure, ensuring both consistency and scalability across environments
  • Certifications in relevant technologies and methodologies, such as certified solutions architect or data engineer credentials from Microsoft Azure, GCP, AWS or Databricks.
  • Ability to inspire, lead, and manage a diverse team of data engineers, fostering an environment that promotes professional growth and high performance
  • Experience working withing an Agile delivery team and effectively collaborating with cross functional teams

Nice to Have:

  • Prior experience in a consultancy setting, demonstrating the ability to navigate the unique challenges and dynamics of consulting with various clients and industries.
  • Knowledge or specialisation in specific industries such as financial services, telecoms, ecommerce or retail, which can help tailor data solutions more effectively to client needs.
  • Experience in building PowerBI semantic models for downstream visualisation consumption.
  • Knowledge and or experience in data management tools such as Azure Purview or Collibra, with exposure to data cataloguing, lineage, and data quality standards.

❔ What’s in it for you?

We’re not a standard consultancy and neither are our benefits – they are enhanced as we pride ourselves on having a people‑first culture which sets us apart from other consultancies and organisations. You can view more on our Benefits here, but as a further insight on how we look after our people, we offer the following support and opportunities:
💰Salary – it’s important, we know! We are open to a range for this role which would generally cover £75,000 to £95,000 per annum (as a full‑time salary, pro rata based on hours less than 37.5hr p/w.)


🏠 (Really) flexible and remote working: most companies say they offer flexible working, but they’ve never experienced flexible working at Intuita. We trust you to work in the way that suits you best and offer flexible hours and part‑time roles to fit your lifestyle. We have UK offices in Newbury, London and Liverpool, which you’re welcome to work from as much as you like; we simply ask that you don’t become isolated – we help in organising a variety of regular social events to ensure we maintain our close‑knit feel.


🧠 Care for your health and wellbeing: we genuinely care about the wellbeing of our team. We offer comprehensive company‑paid medical insurance, free therapy and mental health support via Spill, a team of in‑house Mental Health First Aiders, plus financial education and consultations.


🚀 Incredible training and learning opportunities: our team is full of talented individuals who are genuine experts in what they do. You’ll get to work alongside them and learn from the best, as well as boosting your skills and knowledge with our knowledge sharing sessions, mentoring and company‑paid certifications.


Freedom and empowerment: we allow our consultants to actually be consultants, not just bodies. You’re given the responsibility and accountability to really own problems and are encouraged to explore new directions and opportunities. There are no glass ceilings here and we don’t have salary or promotion review dates – we reward people as and when we see great work!


🧑🤝🧑 A supportive, friendly team: we work hard but enjoy working hard together. We’re a diverse and inclusive team who enjoy silly Slack conversations and regular social events; our relatively flat structure means that everyone has an equal voice.


Our selection process

If you like the sound of Intuita, apply to join us today! Once you have submitted your application, we will be in touch. Please be aware that the timing can vary dependent on the volume of applications that we receive for each role and in some cases, we may start to review applications prior to the closing date.


If you require any support with your application, please contact


#J-18808-Ljbffr

Related Jobs

View all jobs

Principal Consultant - Data Engineering Lead DBT

Principal Consultant- Data Architect, Oracle HCM Cloud, Oracle EBS

Principal Consultant - Data Engineering Lead

Principal Consultant-Data Architect, Oracle HCM Cloud, Oracle EBS-Uk

DBT Lead Data Engineer & Principal Consultant (Remote)

Senior Data Architect — Oracle HCM Cloud & EBS Migrations

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.

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.

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.

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.