Director, Quant Data Engineering

Job Description:

Director, Quant Data Engineering

The Role

The Asset Management Quant Research Engineering team is looking for a Director of Data Engineering who wishes to take on the challenge of building a world-class data operation. We are looking for individuals who bring expertise in data onboarding and quality best practices and the drive to achieve excellence in team building, operations, tooling, and automation. This role is primarily focused on hands-on development and delivery, which requires a combination of both strong technical and influencing skills, as well as participation in architecture, design, analysis, and evangelizing activities.

Primary Location: Boston, MA

Additional Locations; Merrimack, NH; Jersey City, NJ

 

The Expertise and Skills You Bring

• Bachelor's degree (or higher) in either Computer Science, Management Information Systems, Business Information Systems, Mathematics or Finance related field.
• 7+ years of data engineering experience, including in senior and team leadership roles, at peer firms utilizing agile methods and modern SDLC processes to deliver quality technological solutions in a transparent, reliable way.
• Deep domain experience with financial datasets including FactSet, Bloomberg, IBES, CompStat, S&P Global, Worldscope, Morningstar, MSCI, Reuters, IDC, Markit, BARRA, Axioma, Northfield, and PORT
• A proven track record of working with complex data environments and associated technology and analytics infrastructure needed to support these environments.   History of successfully leading and managing complex data initiatives or projects.  Ability to recognize business risk and surface it to key decision-makers.
• A servant leader who is focused on promoting a team culture of accountability and continuous improvement and removing drag forces to enable team success.
• Substantial Investment Management business domain expertise across some combination of research, portfolio management, trading and investment operations.

 

The Value You Deliver

• Deliver datasets from onboarding through mapping and automated DQ so they can be handed off to the Data Operations team for DQ maintenance and consumed by research teams and production.
• Provide data stewardship to other team members and to Data Operations as they review datasets for completeness and quality.
• Design and implement processes and tools for data onboarding and quality, helping to deliver an industry best-practice solution for managing the data lifecycle.
• Produce stand-alone tools that can be used by other teams to automate data quality and discover faults.
• Direct more junior engineers on your team, helping the team to specialize and scale

 

The Team

Asset Management Technology (AMT) provides worldwide technology and support to all the Investment Management, Research, Trading, and Investment Operations functions. This role will be part of our Quantitative Research & Investing Technology team, which is responsible for architecting, developing, and maintaining systems that support quantitative trading.

The base salary range for this position is $103,000-$218,000 per year.  

Placement in the range will vary based on job responsibilities and scope, geographic location, candidate’s relevant experience, and other factors.

Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.   

We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home.  These benefits include comprehensive health care coverage and emotional well-being support, market-leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career.  Note, the application window closes when the position is filled or unposted.

Certifications:

Category:

Information Technology