Principal Data Engineer

RWS
Maidenhead, SL6 1QB, United Kingdom
3 months ago
Applications closed

Related Jobs

View all jobs

Principle AI Data Engineer

Opus Recruitment Solutions London, United Kingdom
Contract

Principal Data Architect DV Cleared

Datatech London, United Kingdom

Data Analyst - Sc cleared

CBSbutler Holdings Limited trading as CBSbutler Reading, Berkshire, United Kingdom
£80 – £83 ph

Data Analyst - Aerospace

CBSbutler Holdings Limited trading as CBSbutler Reading, Berkshire, United Kingdom
£80 – £83 ph

Technical Business Analyst

Premier IT London, United Kingdom
£60,000 – £70,000 pa

Principal Solutions Engineer Enablement Manager

Snowflake London, United Kingdom
£70,000 – £120,000 pa Hybrid
Posted
11 Feb 2026 (3 months ago)

Join to apply for the Principal Data Engineer role at RWS Group.


The Principal Data Engineer will be a foundational technical leader and architect, shaping how we build, scale, and evolve our data infrastructure to unlock insights and drive business value across RWS. This isn't just about writing code; you'll multiply your impact by designing systems that enable teams across the organization to make data-driven decisions, establishing architectural patterns that scale with our growth, and mentoring engineers to raise the capabilities of our entire data organization.


In this role, you'll partner closely with Product, Engineering, Analytics, and Business leaders to translate strategic objectives into robust data solutions. You'll have the autonomy to make architectural decisions that influence how we handle data at enterprise scale, while building the bridges between technical excellence and measurable business outcomes. This is an opportunity to leave a lasting technical legacy while growing the next generation of data engineering leaders.


About Product & Technology


Product & Technology plays a pivotal role in aligning the organization with its strategic objectives and enhancing shareholder value. Product & Technology is responsible for establishing unified standards and governance practices throughout the company. Additionally, we oversee the development and maintenance of core applications essential for the seamless operation of various functions across the organization. We are committed to driving and executing future roadmaps that are in line with the overall strategic direction of RWS.


With a global reach, Product & Technology provides support services to over 7500 end users worldwide. We take pride in managing the information security operation and safeguarding all our assets. Our core functions encompass Enterprise & Technical Architecture, Network & Voice, Infrastructure, Service Delivery, Service Operations, Data & Analytics, Security & Quality Compliance, Transformation, Application Development, Enterprise Platforms. With a dedicated team of over 500 staff, Product & Technology ensures a strong presence across all regions, enabling efficient and effective support to our global operations.


Key Responsibilities



  • Design and develop our data architecture to enable business intelligence, analytics, and ML at scale, making thoughtful trade‑offs between competing approaches and technologies
  • Lead through influence across data, engineering, and product teams, translating technical concepts for diverse audiences and aligning what you build with data strategy with company objectives
  • Drive strategic technical decisions through clear documentation, RFCs, and presentations, anticipating data needs 2‑3 years ahead and identifying when technical debt requires attention
  • Own reliability and performance of critical data systems, building for observability, establishing SLOs, and designing infrastructure that gracefully handles failure
  • Mentor and develop other data engineers, establishing design patterns, conducting architecture reviews, and creating enabling systems that make the entire team more productive
  • Champion operational excellence by implementing best practices for data quality, monitoring, incident response, and cost optimization across our data platform
  • Evaluate and guide technology adoption, assessing emerging tools and determining when they deliver genuine value versus when existing solutions are more appropriate

Skills & Experience



  • Deep systems thinking and architecture experience designing and operating large‑scale data platforms in the cloud, with demonstrated ability to make architectural decisions that balance technical elegance with business pragmatism
  • Exceptional skills in data engineering and its fundamentals including data modelling, pipeline orchestration, distributed systems, and the economics of data infrastructure at scale
  • Cross‑functional leadership skills with proven success influencing technical direction across teams, partnering with diverse stakeholders, and translating between technical and business contexts
  • Track record of multiplying impact through mentorship, documentation, and building enablers and systems that make teams more effective—you’ve helped develop other senior engineers
  • Excellence in communication, with ability to write clear technical documentation, present to technical and non‑technical audiences, and drive consensus on complex decisions
  • Business and product acumen that enables you to prioritize work based on ROI, push back constructively when needed, and connect technical decisions to measurable outcomes

Nice to Have



  • Experience with Google Cloud Platform ecosystem, particularly BigQuery, Dataform, Cloud Composer, or other GCP data services
  • Strong background in metadata management and data cataloging, including tools like DataHub, Alation, or building custom metadata solutions
  • Familiarity with modern data orchestration tools (Airflow, Prefect, Dagster) and DataOps practices
  • Experience with cloud‑native compute patterns including serverless, containerization (Kubernetes), and infrastructure as code
  • Hands‑on experience implementing data mesh principles or other decentralized data architectures
  • Experience with developing or deploying Model Context Protocol for Data assets.
  • Contributions to open source data projects or active participation in the data engineering community

Life at RWS - If you like the idea of working with smart people who are passionate about growing the value of ideas, data and content by making sure organizations are understood, then you’ll love life at RWS.


Our purpose is to unlock global understanding. This means our work fundamentally recognizes the value of every language and culture. So, we celebrate difference, we are inclusive and believe that diversity makes us strong. We want every employee to grow as an individual and excel in their career.


In return, we expect all our people to live by the values that unite us: to partner, putting clients fist and winning together, to pioneer, innovating fearlessly and leading with vision and courage, to progress, aiming high and growing through actions and to deliver, owning the outcome and building trust with our colleagues and clients.


RWS embraces DEI and promotes equal opportunity, we are an Equal Opportunity Employer and prohibit discrimination and harassment of any kind. RWS is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at RWS are based on business needs, job requirements and individual qualifications, without regard to race, religion, nationality, ethnicity, sex, age, disability or sexual orientation. RWS will not tolerate discrimination based on any of these characteristics.


Seniority level


  • Director

Employment type


  • Full‑time

Job function


  • Information Technology

Industry


  • Translation and Localization


#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.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

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.