Data engineer in wealth management

Galilei Investment Office LLP; Greater London; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Office in London

Job summary

Galilei Investment Office LLP in London seeks a data engineer to design and deliver data-driven investment and operational solutions. You will develop data access tools for the Investment and Operations Team, support portfolio analysis and risk reporting, and build data pipelines interfacing with Expersoft and external sources.

Strong Python, SQL and REST API skills are required. Regional flexibility is limited to the London area with an expectation to work in the office four days a week, and

Qualifications

• Bachelor’s degree in Finance, Mathematics, Statistics, Information Systems, Computer Science, Data Science or related fields.
• 1–5 years of data engineering experience.

Responsibilities

• Design and deliver technology solutions across data-driven investment and operational processes.
• Develop data access solutions for the Investment and Operations Team.
• Support data analysis and visualization for portfolio management and risk functions.

Skills

Python

SQL

Git

REST API design

Education

Bachelor’s degree

Tools

Azure

Docker

Pandas/Polars

Matplotlib

Job description

Описание

Galilei Investment Office is an ambitious, dynamic, and innovative FCA regulated, and SEC registered (RIA) wealth management firm headquartered in London. The firm offers investment and portfolio management services to a small number of ultra-high net worth clients. Our core values and philosophy stand on three pillars: Investing with integrity and conviction Outstanding client service Passion and commitment. We are expanding the team and are looking for an individual who shares our values and ambitions.

Задачи

• Design and deliver technology solutions and continuous improvements across data driven investment and operational processes.
• Develop solutions to democratise data access to the Investment and Operations Team.
• Support the Investment Team with data analysis and visualisation for portfolio management and risk functions as needed.
• Develop financial models for market analysis using data from Bloomberg and other sources, such as web scraping and private datasets.
• Maintain and expand data extraction and processing from Galilei’s portfolio management system (Expersoft).
• Develop data cleaning solutions for external reports to enhance compatibility with internal processes.
• Develop automated solutions to identify and flag data discrepancies in portfolio management software.
• Ad-hoc client and investment report preparation, including performance reconciliation.
• Coordinate with the IT service provider to host all software solutions in Galilei's Azure environment, ensuring service reliability, regulatory compliance, and data security.
• Lead the design and development of software solutions to automate internal processes to streamline workflows on both operational and investment portions of the business.
• Document all processes and code implementations clearly and comprehensively for non-technical readers.
• Continue the development and maintenance of the data extraction pipeline from the Portfolio Management System (Expersoft).
• Maintain and enhance existing systems, with a focus on an internal database and API to enable democratised data querying.
• Ensure integrity of data inflow into Galilei’s portfolio management system by liaising with back-office team.
• Provide operational oversight and collaborate with the back-office team to ensure data accuracy in the PMS (Expersoft).
• Classification and mapping of securities to ensure positional alignment across accounts (Expersoft).
• Utilise the portfolio management and reporting system to its full capacity: create, implement, and enhance processes.
• Client reporting: prepare periodic and ad-hoc valuation and performance reports.
• Utilise new software (e.g. LLMs) and techniques to improve team productivity, e.g. automating creation of client presentations and investment research reports.
• Enhance and maintain system for tracking market sentiment and positioning.

Требования

• Experience with programming and data analysis skills, including Python, SQL, Git, and Rest API design/implementation.
• Experience with using LLMs for coding while understanding its pitfalls and how to address them.
• Proficiency in Excel and PowerPoint.
• Bachelor’s degree, preferably in Finance, Mathematics, Statistics, Information Systems, Computer Science, Data Science, or related subjects.
• Must be legally authorized to work in the United Kingdom.
• Experience building databases using structured and unstructured data, including building tools to capture data.
• 1-5 years of experience in data engineering.
• Must be located in commutable distance to London, England, United Kingdom, with the expectation to work from the office at least 4 days a week.
• Excellent analytical and problem-solving skills.
• Ability to develop creative solutions to problems constrained by financial regulation or restricted technological connectivity.
• Strong attention to detail and ability to produce high quality work.
• Excellent communication skills with the ability to work effectively with people at all levels.
• Flexible, high agency, self-motivated, and tenacious.
• Excellent organisational and prioritisation skills.
• Has a structured approach towards systems design and code base development.
• Has a methodologically consistent approach towards work processes and tasks.
• Experience and capability to develop, implement, improve, and document operational processes.
• Affinity and curiosity about financial markets and investment management.

Будет плюсом

• Experience building data extraction pipelines that connect with legacy platforms lacking APIs;
• Experience working with LLM APIs to ingest and process unstructured data;
• Knowledge of and experience with relational databases, ETL pipelines, and data analysis/visualisation tools (Pandas/Polars, Matplotlib);
• Experience building, implementing, and maintaining systems to improve operational efficiency;
• Experience working with Azure cloud infrastructure and Docker containers;
• Experience working with IT systems and processes from an operational and front office perspective;
• Experience in applying AI to program functions, such as reading PDFs into a database and using AI to rank relevance and usefulness of data

Условия

• Base salary: TBC per annum
• Bonus: Discretionary
• Hours of work: Full time (9am to 6pm) with 4 days a week in the office
• Start Date: Immediate
• Holidays: Pro rata of 25 days plus public holidays