VP of Data Engineering
2 weeks ago
Qualifications
Possess a Bachelor's degree or higher in Computer Science, Management Information Systems, Business Information Systems, Mathematics, or a related field.
Have over 7 years of experience in data engineering, including leadership roles within agile environments, focused on delivering top-tier technological solutions using modern SDLC practices.
Demonstrate expertise in industry-standard data lifecycle processes, particularly in automating data quality and utilizing relevant tools.
Exhibit deep domain knowledge of financial datasets such as FactSet, Bloomberg, IBES, CompStat, S&P Global, etc.
Show a consistent track record of navigating complex data environments and managing associated technology and analytics infrastructure, with a knack for identifying and addressing business risks.
Champion a team culture centered on accountability, continuous improvement, and efficiency enhancement, while facilitating team success by eliminating impediments.
Possess substantial expertise in Investment Management, spanning research, portfolio management, trading, and investment operations.
Manage the delivery of datasets, ensuring they undergo proper onboarding, mapping, and automated data quality processes before being handed off to Data Operations for maintenance and consumption by research teams and production.
Provide data stewardship to team members and Data Operations, ensuring datasets meet completeness and quality standards.
Develop and implement efficient processes and tools for data onboarding and quality control, aiming to establish industry best practices for managing the data lifecycle.
Create standalone tools for automating data quality checks and fault discovery, benefiting other teams within the organization.
Guide and mentor junior engineers within the team to enhance specialization and scalability.
The Team
This team offers global technology support for Investment Management, Research, Trading, and Investment Operations functions. This position will be part of the Quantitative Engineering team, responsible for designing, developing, and maintaining systems supporting quantitative trading.
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