data engineer for investment data

The client is a global investment management company headquartered in London. It manages over $228 billion in assets and serves institutional investors, pension funds, wealth managers, and other sophisticated clients worldwide. The firm specializes in quantitative investing, alternative investments, systematic trading strategies, and technology-driven asset management. Data science, machine learning, and AI are core components of its investment and research processes.

• Provide first-level data support to portfolio managers, researchers, traders, engineers, and data scientists across the firm
• Lead the onboarding and integration of financial and alternative datasets, including reference, ESG, market, and alternative data, into the data lakehouse
• Design and build ETL pipelines using industry-standard and proprietary technologies
• Work with engineering teams to define and optimize data models, schemas, and workflows
• Identify and resolve data quality issues proactively, and drive data quality management with engineering
• Own and enhance security master content and identifier mapping tools, keeping data accurate and consistent across systems
• Manage market data permissions, improve usage tracking, analyze usage patterns, and optimize cost attribution and charge models
• Curate and maintain a metadata catalogue and knowledge base, and support data lineage and governance
• Automate daily tasks and help build a scalable data ingestion and management framework, including dashboards and an optimized ongoing data management process
• Learn the firm’s vendor data sources and act as a subject matter expert on selected projects, providing high-quality data analysis and quality assurance
• Comply with company policies on risk, compliance, and confidentiality, and escalate risk issues appropriately

• 3+ Years of experience in a data management, data engineering, or analyst role
• A strong academic record and a higher education degree with substantial mathematics and computing content, such as Computer Science, Mathematics, or Engineering
• 2+ Years of experience with data and data wrangling in a finance or finance-related firm
• Experience with ETL pipelines and data lakehouse concepts
• Programming skills in Python and SQL
• Strong problem-solving and analytical skills
• Strong written and verbal communication skills
• Self-organization and the ability to manage time across multiple projects and competing business priorities
• Familiarity with financial data aggregators such as Refinitiv, FactSet, S&P, IHS, or Bloomberg
• Working knowledge of databases, Linux/UNIX, Git, and Jira
• Commitment to excellence, integrity, and personal accountability, including escalating issues when appropriate
• Client focus, understanding internal stakeholders, speaking their language, and managing their expectations
• Original and innovative thinking, a positive attitude, and an interest in continuously building new skills
• Comfortable in an entrepreneurial environment; a collaborative and diligent team member
• Passion for using science, technology, and data to improve the investment process
• Будет плюсом: Interest in or exposure to alternative, ESG, and market data

• Условий в вакансии нет