Staff Data Engineer in London

Staff Data Engineer in London

London Full-Time 98450 - 130000 £ / year (est.) Home office (partial)
United States Digital Space LLC

At a Glance

  • Tasks: Lead the technical strategy for our data platform and tackle complex data challenges.
  • Company: Join a forward-thinking company transforming the future of work with AI and automation.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Other info: Dynamic team environment focused on trust, empathy, and collaboration.
  • Why this job: Make a real impact by shaping data architecture and driving innovation.
  • Qualifications: Experience in building data platforms and strong problem-solving skills.

The predicted salary is between 98450 - 130000 £ per year.

ABOUT BEAMERY

With the rapid expansion of AI and automation, the future of work has never been more challenging for organizations. The company’s unique jobs, skills and tasks data platform helps organizations navigate these challenges and make more informed decisions across Talent Lifecycle Management. Our solutions power recruitment, mobility, upskilling, diversity, work architecture and workforce planning for some of the world’s most forward-thinking companies. We believe that where you work is much more than just a job. Millions of people are being left behind every day in their careers, and we’re on a mission to fix this by creating equal access to meaningful work, skills and careers for all. We are an equal opportunity employer committed to building a representative company, creating an equitable, inclusive and engaging environment for our people.

What’s ahead — and why it’s an exciting time to join the team:

  • Deepening our native integrations with SAP, Workday, Microsoft, and LinkedIn to seamlessly embed our skills intelligence into the platforms where critical workforce decisions are made.
  • Embedding our agentic AI to help customers plan smarter for the future—powering workforce strategies, internal mobility, and skills forecasting.
  • Advancing our use of proprietary LLMs and knowledge graph technology to help organizations unlock broader talent pools, make fairer decisions, and expand access to opportunity at scale.

About the opportunity

Our data platform powers the company’s reporting and underpins our AI strategy. We’re hiring a Staff Data Engineer to set its technical direction. This is our most senior individual contributor role in data engineering. You’ll own the platform’s long-term architecture, make the calls that are expensive to reverse, and lead the work that follows. You’ll also partner with EPD leadership (Engineering, Product, and Design) on work that crosses team boundaries, and on keeping the platform aligned with company strategy. The platform exists so everyone at the company can make faster decisions with data they trust. The role suits someone energised by ambiguity who measures impact by what the organisation can do rather than what they personally shipped.

What will you be doing at the company?

  • Own the technical strategy for the data platform.
  • Define the multi-quarter architectural vision, build the case for investment with EPD leadership, and sequence delivery incrementally rather than as a big-bang migration.
  • Take on the work with no established playbook and turn it into designs the team can execute.
  • Expect challenges around multi-tenant consistency, correctness at scale, performance ceilings, and data modelling for AI and agentic workloads.
  • Architect the analytics, semantic, and AI data layers.
  • Define how core business metrics, feature usage signals, and skills and task intelligence data are modelled, governed, and exposed as trustworthy products to BI, self-service, and AI consumers.
  • Set standards that scale beyond your team.
  • Establish the architectural patterns, modelling conventions, and data contracts other teams adopt, favouring guardrails over review gates.
  • Grow senior engineers into stronger technical decision-makers through design review, pairing, and mentorship.
  • Own reliability and trust at the platform level.
  • Set our approach to observability, data quality, SLAs, and incident response; lead RCAs on the most serious failures and drive the systemic fixes that prevent recurrence.

What we’re looking for

You’re a staff-level data engineer who has built and run data platforms for internal and external consumers. You’ve built architectures that held up as they grew with a focus on data warehousing, data lakes, and both real-time and batch processing. Teams bring you their hardest data problems. You’ve made the hard tradeoffs in distributed, multi-tenant systems and lived with the consequences. You’re just as comfortable in production: tracing how one upstream failure ripples through to customers, and making sound calls under pressure. Your impact isn’t measured in code alone. You’ve led initiatives across team boundaries without formal authority, working directly with principal engineers, platform teams, and data scientists, and treating their constraints as part of your design problem. You’ve made architectural decisions others built on for years, and driven modernisation while balancing new technology against real delivery risk. You work with minimal direction, explain tradeoffs and risks credibly to executive audiences, and change your mind as readily as you defend a position.

Previous professional experience:

  • Data transformations using dbt, including patterns for large, complex projects
  • Data storage (SQL / NoSQL): schema design, modelling at scale, and multi-tenant isolation
  • Back-end engineering: Python (nice to have: Typescript/Node.JS)
  • Pipelines: streaming, CDC, correctness, replayability, and evolution over time
  • Data quality and observability: validation, testing, data contracts, monitoring, alerting, and incident response
  • Infrastructure as code and containerisation (Terraform, Kubernetes)

Our data stack

Our stack will change as we grow, and you’ll be shaping those changes. The ability to learn new tools matters more than experience with any specific one.

  • DBT for data modelling and transformation
  • BigQuery data warehouse
  • Kafka for data streaming between systems
  • PostgreSQL & MongoDB for databases
  • Typescript/Node.JS on the backend
  • Kubernetes
  • Python
  • Segment for customer-centric event collection

The company is open to engage with direct employment or contractors for this position in order to find the right fit candidate to join our team. The company is for Everybody. Diversity and open expression are fundamental to us. We acknowledge the challenges in our industry and strive to develop an inclusive culture where everybody can contribute. We are dedicated to creating an inclusive environment for everyone, regardless of ethnicity, religion, color, sexual orientation, gender identity, race, national origin, age, disability status, or caregiver status. If, for whatever reason, you need us to make reasonable adjustments and adaptations to our recruitment process, please email. Visit our Diversity, Equality and Inclusion page to learn more about progress and commitments.

Compensation: £98,450 – £130,000

Staff Data Engineer in London employer: United States Digital Space LLC

United States Digital Space LLC is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration in the heart of Greater London. With a strong focus on employee well-being and flexible work options, we provide ample opportunities for professional growth and development, making it an ideal environment for those looking to make a meaningful impact in the field of AI-enabled SaaS engineering.

United States Digital Space LLC

Contact Details:

United States Digital Space LLC Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Data Engineer in London

Get Involved in Data Science Meetups

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like United States Digital Space LLC.

Apply Directly through Our Website

When you find a suitable opening like Staff Data Engineer at United States Digital Space LLC, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Staff Data Engineer in London

Data Engineering
Data Platform Architecture
Data Warehousing
Data Lakes
Real-time Processing
Batch Processing
Data Transformations using dbt

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Craft a Tailored Cover Letter:For a full-time role at United States Digital Space LLC, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at United States Digital Space LLC. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at United States Digital Space LLC

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at United States Digital Space LLC!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.