As a Data Engineer, you will work closely with researchers to enhance our Equity Data Framework, which underpins the firm’s analytic and research platform. You will be part of a team dedicated to a specific strategy but will regularly engage with challenges relevant across the firm.

Essential Requirements:

Proficient in Python, with a strong command of data manipulation and analysis libraries, notably Polars, Pandas, and NumPy.
Familiarity with data related to equities, especially corporate actions, and experience working with third-party data sets.
Ability to find effective solutions when resources are limited, and proactively contribute to the enhancement of the research framework.

Skills:

Experience with database systems, query engines, and data warehousing, particularly in handling large volumes of structured data.
Proficient in database management and optimization, with experience in data validation and integration within complex dependency graphs.
Experience in troubleshooting, performance tuning, and optimizing data-related systems.
Comfortable working with command line.
Strong problem-solving and debugging skills.

Job Duties:

Maintain and enhance the research framework for global equities.
Optimize the collection, processing, validation, manipulation, and presentation of static and historical data for Global Equities.
Apply corporate actions to prices, portfolios, ETF baskets, reference data, and other relevant datasets.
Create and maintain datasets relating to global equities.
Develop and integrate validation tests into the dependency graph.
Enhance the performance and flexibility of the query engine used by the team.