Quantitative Analyst/Data Engineer

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day.

One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We’re devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.

Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

Summary:
 

We seek a teammate with the ability to design, construct, and analyze data pipelines to support our quantitative infrastructure with a passion for system architecture with an entrepreneurial mindset. The associate will have extensive interaction other teams within the Chief Investment Office (CIO) such as due diligence, portfolio construction, platform management, technology, and risk teams. The associate will be expected to manage multiple projects simultaneously and discover innovative solutions to complex problems.

They are expected to help manage the team’s overall ability to meet deadlines and milestones, and will actively lead and work to transition code, scripts, tables and processes in coordination with other SO&DA resources.  The associate will be expected to manage multiple projects simultaneously, discover innovative solutions to complex problems, elevate and improve existing processes and must be comfortable working in a fast-paced environment.

Responsibilities:

• Analyze and organize raw data from different sources (Vendors, data delivery methods, etc.)
• Maintain SQL databases.
• Build data systems and pipelines
• Automate reports and processes to run with varying frequencies.
• Monitor and debug processes and report the problem to the corresponding responsible parties.
• Communicate to technology the needs and specifications of processes.
• Explore ways to enhance data quality, reliability, and efficiency
• Identify opportunities for data acquisition
• Develop analytical tools and programs
• Collaborate with data scientists and architects on several projects
• Perform unit tests and conduct reviews with other team members to make sure your code is rigorously designed, elegantly coded, and effectively tuned for performance.

 Qualifications

Minimum Requirements

• BSc in Computer Science, IT, or relevant field required
• Minimum of 8+ yrs. total experience
• At least 5+ years' experience in Extract, Transform, Load (ETL) and/or Extract, Load, Transform (ELT) processes.
• Proficient in data engineering practices and have extensive experience of using design and architectural patterns.
• Experience working with database management languages (SQL, NoSQL).
• Extensive experience with object-oriented programing (OOP)/Scripting languages such as R, Python, Bash, and/or Matlab
• Technical expertise with data models, data mining, and segmentation techniques.
• Experience working in multiple technology deployment lanes (development through production) is required.
• Experience working with Git/Bit Bucket and code versioning.

Preferred additional qualifications

• MS in Computer Science, Engineering, or relevant field
• Data engineering certification (e.g IBM Certified Data Engineer) is a plus.
• Familiarity with internal or vendor data (FactSet, Morningstar, Bloomberg, API usage) is a plus but not required.
• Experience with creating visualization dashboards (Tableau)
• Hands-on experience in database design is a plus.
• Extreme attention to detail and organizational prowess
• Ability to work both independently and in teams on projects executing on-time and with precision