At a Glance
- Tasks: Build and manage data models on BigQuery for trading and finance.
- Company: Global exchange with a focus on AI and data innovation.
- Benefits: Competitive pay, exciting projects, and a chance to shape the future of FinTech.
- Other info: Opportunity to work on greenfield projects in a dynamic environment.
- Why this job: Join a cutting-edge team and make an impact in the AI-driven financial world.
- Qualifications: 5+ years in data engineering with GCP and BigQuery experience.
The predicted salary is between 80000 - 98000 £ per year.
A global exchange with a media and market data business attached are building out their AI & Data Platform team and need multiple Senior Data Engineers based in London to help the business move to Google Cloud and become AI-ready for the multi-agent projects in the pipeline.
If you're at a Google Cloud partner and you've spent years implementing this stack for other businesses, BigQuery, Composer, Looker, enterprise agent platform then this is the role where you can own it. You build it, you run it, and the output feeds real trading and compliance decisions on a live, regulated exchange operating at huge scale.
What you'll be doing:
- Building and owning dbt models on BigQuery across trading, finance, and regulatory domains
- Supporting both BI users (Looker dashboards) and AI agents consuming governed data via MCP
- Owning pipeline reliability during London hours; incident response, schema drift, reconciliation breaks
- Semantic layer work that needs to be precise enough for AI agents to query correctly
What they're looking for:
- ~5+ years in data engineering, production pipelines, layered architectures
- ~GCP / BigQuery hands-on experience, as well as other Google Cloud services.
- ~Looker / LookML is a plus
If you're looking to join a business with plenty of greenfield projects, who are serious about AI and likes the idea of being in the FinTech world, this could be a great fit.
Comp is competitive and reflective of experience.
Senior Data Engineer (contract) in London employer: Orbis Group
Join a forward-thinking global exchange in London, where innovation meets opportunity. As a Senior Data Engineer, you'll thrive in a dynamic work culture that champions collaboration and creativity, while contributing to cutting-edge AI and data projects. With competitive compensation and ample opportunities for professional growth, this role offers a unique chance to make a significant impact in the FinTech sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer (contract) in London
✨Showcase Your Skills with a Public Portfolio
As a freelancer in data science, having a killer portfolio is essential. Showcase your projects on platforms like GitHub or create a personal website that details your work and techniques. This gives potential clients a clear picture of what you can do and helps you stand out from the competition.
✨Get Involved in Data Science Communities
Tap into online forums like Kaggle or Stack Overflow. Not only can you showcase your expertise, but you can also connect with other data scientists and potential clients. Plus, participating in competitions and discussions can elevate your profile in the field.
✨Leverage Local Networking Opportunities
Keep an eye out for local data science meetups or tech events in your area. These are golden opportunities to meet potential clients and collaborators face-to-face. Plus, who doesn't love a bit of networking over pizza and drinks?
✨Pitch Your Services Directly to Companies
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We think you need these skills to ace Senior Data Engineer (contract) in London
Some tips for your application 🫡
Showcase Your Projects:When applying for a freelance data science role like Senior Data Engineer (contract) at Orbis Group, it’s crucial to highlight your projects. Include a portfolio that features at least two or three projects involving data analysis, machine learning, or visualisation. Make sure to describe the tools and methodologies you used, so we can see your skills in action!
Quantify Your Achievements:Freelance gigs, especially in data science, often ask for proven results. In your CV, include any relevant metrics or outcomes from your previous work. Did your analysis help reduce costs by a certain percentage? Or did your predictive model improve performance? Numbers speak volumes!
Introduce Your Style:Since freelancing is all about your individual style and approach, use your cover letter to share how you tackle data problems. This is your chance to let us know how you think, your creative problem-solving methods, and how you would approach a project at Orbis Group.
Be Real About Your Rates:When you send in your application, don’t forget to mention your freelance rates and availability. We appreciate clarity up front, and it helps us gauge if you fit within our budget and timeline. Being transparent in this aspect shows professionalism and readiness!
How to prepare for a job interview at Orbis Group
✨Show Off Your Data Wizardry
As a freelancer in data science, you'll want to present a portfolio that showcases your best projects. We should pull together examples where you tackled real problems with data analytics, machine learning models, or visualisations. It's all about demonstrating your skills in action!
✨Be Ready to Dive Deep into Technical Questions
Expect to encounter some technical grilling during the interview. Prepare to discuss statistical methods, algorithms, or maybe even tackle a live coding challenge. We should brush up on tools like Python, R, or SQL—those are key players in the data science field. Don't just know them; be ready to explain your thought process!
✨Help Them Understand Your Work Style
Freelance gigs often mean you'll be working independently, so we need to convey our self-motivation and time management skills. Be prepared to talk about how you’ve handled multiple projects or met tight deadlines before. Sharing your approach to client communication can also give them confidence in your ability to deliver remotely.
✨Pitch Your Value Proposition
When freelancing, it’s crucial to clearly articulate what makes you unique. We should highlight not just technical skills but also the business impact of our projects. Think of a couple of stories where your data insights drove decision-making—this can be a game changer in showing why they should choose you for their freelance needs!
