DATA ENGINEERING CONSULTANT

Position Description.
The Role The Asset Management Quant Research Engineering team is looking for a Senior Data Engineering Consultant 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.
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.
Your future duties and responsibilities.
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.
• Design and implement processes and tools for data onboarding and quality, helping to deliver an industry best-practice solution for managing the data lifecycle.
• Provide data stewardship to other team members and to Data Operations as they review datasets for completeness and quality.
• Produce stand-alone tools that can be used by other teams to automate data quality and discover faults.
Required qualifications to be successful in this role.
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.
• 5+ years of Data Engineering experience, at peer firms utilizing agile methods and modern SDLC processes to deliver quality technological solutions in a transparent, reliable way.
• Demonstrable mastery of industry best practices in the data lifecycle, including data quality automation and tooling.
• Demonstrated 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.
Ability to recognize business risk and surface it to key decision-makers.
• Substantial Investment Management business domain expertise across some combination of research, portfolio management, trading and investment operations.
Skills.
Data Engineering Data Quality Management What you can expect from us.
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