Data Engineer Lll

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!

Job Description:

This job is responsible for driving efforts to develop and deliver complex data solutions to accomplish technology and business goals. Key responsibilities include leading code design and delivery tasks with the integration, cleaning, transformation and control of data in operational and analytical data systems. Job expectations include liaising with vendors and working with stakeholders and Product and Software Engineering teams to implement data requirements, analyzing performance, and researching and troubleshooting issues within system engineering domains.

This job is responsible for driving efforts to develop and deliver complex data solutions to accomplish technology and business goals. Key responsibilities include leading code design and delivery tasks with the integration, cleaning, transformation and control of data in operational and analytical data systems. Job expectations include deployment of advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to deliver insights. This role often possesses a degree in hard science or another heavy quantitative business or social discipline. Able to work independently on complex projects.

Responsibilities:• Leads story refinement and delivery of requirements through the delivery lifecycle and assists team members in resolving technical complexities

• Codes complex solutions to integrate, clean, transform, and control data, builds processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, assembles complex data sets, and communicates required information for deployment

• Leads documentation of system requirements, collaborates with development teams to understand data requirements and feasibility, and leverages architectural components to develop client requirements

• Leads testing teams to develop test plans, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and leads triage of underlying causes

• Leads work efforts with technology partners and stakeholders to close gaps in data management standards adherence, negotiates paths forward by thinking outside the box to identify and communicate solutions to complex problems, and leverages knowledge of information systems, techniques, and processes

• Leads complex information technology projects to ensure on-time delivery and adherence to release processes and risk management and defines and builds data pipelines to enable data-informed decision making

• Mentors Data Engineers to enable continuous development and monitors key performance indicators and internal controls

• Leads story refinement and delivery of requirements through the delivery lifecycle and assists team members in resolving technical complexities

• Codes complex solutions to integrate, clean, transform, and control data, builds processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, assembles complex data sets, and communicates required information for deployment

• Leads documentation of system requirements, collaborates with development teams to understand data requirements and feasibility, and leverages architectural components to develop client requirements

• Leads testing teams to develop test plans, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and leads triage of underlying causes

• Leads work efforts with technology partners and stakeholders to close gaps in data management standards adherence, negotiates paths forward by thinking outside the box to identify and communicate solutions to complex problems, and leverages knowledge of information systems, techniques, and processes

• Leads complex information technology projects to ensure on-time delivery and adherence to release processes and risk management and defines and builds data pipelines to enable data-informed decision making

• Mentors Data Engineers to enable continuous development and monitors key performance indicators and internal controls

This position may also have responsibilities for managing associates. At Bank of America, all managers at this level demonstrate the following responsibilities, in addition to those specific to the role, listed above.

• Diversity & Inclusion Champion: Creates an inclusive team where members are treated fairly and respectfully.

• Manager of Process & Data: Demonstrates and expects process knowledge, data driven decisions, simplicity and continuous improvement.

• Enterprise Advocate & Communicator: Delivers clear and concise messages that motivate, convey the "why" and connects contributions to business results.

• Risk Manager: Leads and encourages the identification, escalation and resolution of potential risks.

• People Manager & Coach: Knows and develops team members through coaching and feedback.

• Financial Steward: Manages expenses and demonstrates an owner's mindset.

• Enterprise Talent Leader: Recruits, on-boards and develops talent, and supports talent mobility for career growth.

• Driver of Business Outcomes: Delivers results through effective team management, structure, and routines.

Required Qualifications:

• Five years experience in a data science or modelling role

• DevOps Practices

• Three plus years with Machine Learning/Artificial Intelligence

• Proficient with Python

Skills:

• Analytical Thinking

• Application Development

• Data Management

• DevOps Practices

• Solution Design

• Agile Practices

• Collaboration

• Decision Making

• Risk Management

• Test Engineering

• Architecture

• Business Acumen

• Data Quality Management

• Financial Management

Shift:

1st shift (United States of America)

Hours Per Week:

40