At a Glance
- Tasks: Build and scale data capabilities for a cutting-edge investment platform.
- Company: Join Fundment, a fast-growing wealth infrastructure company transforming the UK market.
- Benefits: Enjoy competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative team environment with meaningful ownership and visible impact from day one.
- Why this job: Make a real impact on financial data solutions that shape the future of wealth management.
- Qualifications: 3-5 years in data engineering, strong SQL and Python skills, and experience with cloud platforms.
The predicted salary is between 60000 - 75000 £ per year.
Fundment is a fast-growing wealth infrastructure company transforming the £3 trillion UK wealth management market.
Our proprietary investment platform combines modern technology with exceptional service to help financial advisers deliver better outcomes for their clients.
As we scale, data is becoming one of our most important strategic assets.
We are growing our Data, Analytics&AI function to build the trusted data foundations that power our platform, improve decision-making, and enable the next generation of intelligent investment and operational products.
Purpose of the Role
We are looking for a Securities Data Engineer to help build and scale the data capabilities at the heart of Fundment’s investment platform.
This is a high-impact, hands-on role focused on designing, building and operating the pipelines, models and controls that power securities, market, pricing and reference data across the business.
Your work will support investment products, operational processes, reporting, analytics and future AI-powered capabilities.
You will work closely with teams across Investments, Product, Operations and Engineering to ensure Fundment’s data is accurate, reliable, scalable and ready to support our next stage of growth.
Key Responsibilities
- Build and maintain robust pipelines for securities, market, pricing and reference data from internal and external sources.
- Develop core data models covering securities, securites events (e. g. corporate actions, bond coupon payments), issuers, listings, identifiers, instrument hierarchies and related reference datasets.
- Create reliable rule-processing and data quality controls that produce accurate, auditable and reproducible outputs.
- Support key investment and operational workflows, including portfolio management, trading, reporting, corporate actions, identifier mapping and vendor reconciliation.
- Contribute to the design and development of Fundment’s modern cloud-based data platform.
- Build curated datasets, transformation layers and semantic models that support analytics, reporting and AI use cases.
In particular, develop and maintain data models that support portfolio holdings, benchmark, investment product and performance analytics.
- Implement monitoring, testing and observability to ensure data pipelines and products run reliably in production.
- Help establish data engineering standards, modelling patterns and best practices across the platform.
- Collaborate with Product, Engineering, Operations, Investments, analysts and data scientists to turn business needs into scalable technical solutions.
- Required Skills / Experience
- Proven experience (3–5+ years) in data engineering, software engineering or financial data engineering.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Finance or equivalent practical experience.
- Deep experience working with time-series data for securities, handling corporate actions, bond coupon payments, reconciliations, quality assurance etc
- Experience modelling portfolio holdings, benchmark, investment product and performance data.
- Strong proficiency in SQL and Python for data processing, modelling and analysis.
- Experience building and maintaining production-grade data pipelines.
- Experience with cloud-based data platforms like GCP, AWS or Azure.
- Experience building data transformation workflows using tools such as dbt or equivalent frameworks.
- Understanding of data modelling principles, including historical data management and auditability.
- Experience with source control, testing, CI/CD and software engineering best practices.
- Excellent written and verbal communication skills.
- Preferred Skills / Experience
- Experience in a startup or high-growth environment.
- Experience with data infrastructure (Spark, Dataflow or other big data framework) on cloud platforms.
- Experience building and maintaining data transformation layers using dbt.
- Experience with data visualisation tools such as Looker.
- Experience with Infrastructure as Code tools like Terraform.
- Experience with Spark, Py Spark or other distributed processing technologies.
- Familiarity with data governance, lineage and cataloguing tools.
- Knowledge of financial services regulation, including FCA and GDPR considerations.
- Exposure to AI/ML data pipelines or data platforms supporting AI applications.
Why Join Us?
This is an opportunity to work on data infrastructure that sits at the core of a growing wealth technology platform.
You will have meaningful ownership from day one, solving complex financial data problems that directly affect our products, clients and operations.
You will join a collaborative, ambitious and supportive team where your ideas matter, your work has visible impact, and you can help shape the future of Fundment’s data platform as the business scales.
We are happy to consider any reasonable adjustments applicants may need during the recruitment process.
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Securities Data Engineer employer: Fundment
At Fundment, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to thrive. As a Lead Python Engineer, you will not only engage in hands-on coding but also play a pivotal role in mentoring a talented team, ensuring your professional growth alongside theirs. Located in a vibrant tech hub, we offer competitive benefits, flexible working arrangements, and opportunities for continuous learning, making us an exceptional employer for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Securities Data Engineer
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Securities Data Engineer at Fundment.
✨Leverage Professional Networks
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 Fundment.
✨Apply Directly through Our Website
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We think you need these skills to ace Securities Data Engineer
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Fundment, 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 Fundment. 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 Fundment
✨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 Fundment!
✨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.
