At a Glance
- Tasks: Design and develop scalable data pipelines for trading and portfolio management.
- Company: Dynamic trading house with a focus on innovation and collaboration.
- Benefits: Competitive daily rate, hands-on experience, and exposure to cutting-edge technologies.
- Other info: On-site role in London with excellent opportunities for professional growth.
- Why this job: Join a fast-paced team and make a real impact in the financial services sector.
- Qualifications: 5+ years in Data Engineering, strong Python skills, and cloud platform experience.
The predicted salary is between 60000 - 80000 £ per year.
A trading house are looking for a Data Engineer to join their Front Office Data & Analytics Engineering team, working alongside Quantitative Researchers and engineering colleagues to build the data platforms and services that support research, trading and portfolio management. This is a hands‑on role where you will design, develop and support scalable data pipelines and cloud‑based solutions, ensuring high‑quality, reliable and timely data is available to power investment decision‑making across the business. You will take ownership of solutions throughout their lifecycle, from design and implementation through to testing, deployment and production support.
Working with technologies including Python, Snowflake, MongoDB and AWS, you will help evolve our data architecture, improve data quality through validation and monitoring, and contribute to a collaborative, fast‑paced engineering environment focused on delivering robust, investment‑enabling data solutions.
Required Experience- 5+ years' experience in Data Engineering or Software Engineering, ideally within financial services, with strong Python development skills and software engineering best practices (version control, testing and CI/CD).
- Proven experience designing, building and supporting scalable cloud‑based data platforms and pipelines, preferably on AWS, including containerised deployments using Docker.
- Strong experience working with Snowflake and NoSQL databases, particularly MongoDB, with a solid understanding of data modelling, governance and lifecycle management.
- Good understanding of financial markets and investment data, with the ability to work closely with Quantitative Researchers and translate business requirements into scalable technical solutions.
- Demonstrated ownership mindset with excellent problem‑solving, communication and stakeholder management skills, including experience supporting production environments and resolving business‑critical data issues.
This is a £700-800/day contract role based in London; on‑site.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer – Front Office Data & Analytics 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 Data Engineer – Front Office Data & Analytics in London
Some tips for your application 🫡
Showcase Your Projects:When applying for a freelance data science role like Data Engineer – Front Office Data & Analytics at Alexander Ash Consulting, 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 Alexander Ash Consulting.
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 Alexander Ash Consulting
✨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!
