About the Client
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.
Responsibilities
•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
Requirements
•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
Nice to Have
•Interest in or exposure to alternative, ESG, and market data
Conditions
No conditions specified in the posting.
