Job roles: Data Engineer
Experience level: Mid, Senior
Tech stack/tooling used: SQL, Python, Data Modeling, dbt, Spark, GCP, AWS, Azure, CI/CD, Pyspark
Core skills considered: SQL, Python, Data Modeling, dbt, Spark
Other skills considered: GCP, AWS, Azure, CI/CD, Pyspark
Employment type: Permanent
Remote working: Hybrid
Visa sponsorship: Not available
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.
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.
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.
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.
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, PySpark 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.
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.
Be part of a modern, inclusive, high-trust engineering culture
Take ownership and ship code that directly improves client outcomes
Work with a smart, friendly team that values balance, growth, and support
Pension 6% employer contribution, minimum 2% employee contribution.
BUPA Private Health Insurance – fully paid for by the company, for you and your immediate family.
Medicash Cashplan – fully paid for by the company, for you and your immediate family.
Travel insurance – fully paid for by the company, for you and your immediate family.
Life Assurance – 4 x base salary.
Employee Assistance Programme
28 days annual leave plus bank holidays.
Paid compassionate leave – up to 5 days per year.
Enhanced paternity/maternity/adoption leave – 16 weeks at full pay after 12 months of service.
Jury service – 10 days at full pay.
Hybrid working arrangements – 3 days per week in the Fitzrovia office.
Coaching&Counselling sessions
Training Budget
Annual pay review
Annual training budget
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