Data Engineer - Data Management

Tasks

As a Data Engineer, you will use your technical and business skills to source and support data used by investment teams and provide support to enable the delivery of high-quality data analysis and quality assurance. You will work in a team responsible for investment data governance, including data capture, financial and alternative data quality assurance, security monitoring, and data lineage. Responsibilities include:

• Deliver world-class data support to portfolio managers, researchers, traders, engineers, and data scientists across the enterprise.
• Manage the onboarding and integration of various financial and alternative data sets.
• Design and build ETL pipelines using industry standard and proprietary technologies; define and optimize data models, schemas, and workflows with engineering teams.
• Proactive monitoring and resolution of data quality issues before they impact downstream users; data quality management and control with engineering teams.
• Own and improve security master content and data quality monitoring tools to ensure accuracy and efficiency.
• Manage client data permissions, improve usage tracking, analyze usage behavior patterns, and optimize cost tasks.
• Curate and maintain a metadata catalog and knowledge base, and drive forward the potential automation of daily tasks.

Requirements

Essential:

• Experience with data collection, management, and analysis, preferably in the financial industry.
• Strong knowledge of Python and SQL.
• Expertise in ETL tools and technologies.
• Strong interpersonal skills; able to establish and maintain close working relationships with quantitative analysts, technology, traders, and other senior stakeholders.
• Strong analytical thinking and responsibility for results.
• Strong written and oral communication skills.

Desirable:

• Working knowledge of data modeling, data lakehouse, Linux/Unix, SQL, 3+ years is preferred.
• Familiarity with one or more relevant database technologies, e.g., Apache Hadoop, PostgreSQL, Snowflake.
• Experience working with large and structured data sets.
• Practical experience with financial data providers and understanding of market data structures.
• Experience with data warehouse design; proven ability to work effectively across different teams and seniority levels.

We offer

A work environment that promotes equal opportunities and a culture that encourages work-life balance through our charitable and global initiatives, while advancing your career through professional development and flexible working conditions.