Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Principal Data Engineer, Consulting

Anson McCade
Glasgow
5 months ago
Applications closed

Related Jobs

View all jobs

Principal Data Architect

Data Architect - Cloud

Data Architect

Data Architect

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer – Consulting | £90K–£105K | London / Leeds / Bristol


Our client, a global leader in digital transformation consulting, is hiring aPrincipal Data Engineerto lead the design and delivery of advanced cloud-native data solutions. Based inLondon, Leeds, or Bristol, this is an opportunity to work on greenfield projects that solve complex data challenges across enterprise environments.


💼Salary: £90,000 – £105,000

📍Location: London, Leeds, or Bristol

  • Hybrid (2 days per week in office)

🛡️Must be eligible for SC (Security Check) clearance


🧠 The Role

As aPrincipal Data Engineer, you’ll propose and implement solutions using a range of AWS infrastructure. Working within a multidisciplinary consulting team, you’ll collaborate directly with clients to shape strategy, drive delivery, and guide internal engineering standards.


Your responsibilities:

  • Build and maintain large-scale data lakes and ETL pipelines usingAWS S3, Redshift, Glue, Lambda, DynamoDB, and Matillion
  • Translate client requirements into scalable and secure data architectures
  • Drive infrastructure-as-code and CI/CD deployment practices
  • Process structured and semi-structured data (JSON, XML, Parquet, CSV)
  • Maintain metadata, build data dictionaries, and ensure governance is embedded by design
  • Work across industries in fast-paced, high-value engagements


ThisPrincipal Data Engineerwill bring:

  • Extensive experience withETL/ELT pipelinesand data transformation patterns
  • Proficiency inAWS cloud services, particularlyRedshift, Glue, Matillion, and S3
  • Strong command of data quality, data lineage, and metadata practices
  • Fluency in database technologies (both relational and NoSQL)
  • Experience with Linux environments and data visualisation tools (e.g.Tableau, QuickSight, Looker)


Bonus points for:

  • Familiarity withHadoop, Spark, or MapReduce
  • Exposure todata APIsand microservice-based architectures
  • AWS certifications (Solutions Architect Associate, Big Data Specialty)
  • Experience or interest inmachine learning data pipelines


🚀 Why Join?

As aPrincipal Data Engineer, you’ll:

  • Lead the architecture of cloud-first data ecosystems for top-tier clients
  • Be part of a supportive, knowledge-sharing engineering team
  • Enjoy hands-on influence across the full data lifecycle—from ingestion to insight
  • Contribute to transformative programs in sectors such as financial services, retail, and government
  • Access a clear path to leadership and continuous learning across cloud and consulting domains


Ready to lead next-generation data platforms?

If you’re eligible forSC clearance, and want to work at the intersection of cloud, data, and strategy—thisPrincipal Data Engineerrole is your next step.


Apply today and build what’s next.

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.

Jobs

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

🍪 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.