Assistant Vice President; Data Engineer

Bank of America•Charlotte, NC

2d•Hybrid

About The Position

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve. Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us! Responsibilities Develop and deliver data solutions to accomplish technology and business goals and initiatives. Perform code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems. Work with stakeholders and Product and Software Engineering teams to aid with implementing data requirements, analyzing performance, and researching and troubleshooting data problems within system engineering domains. Work across development teams to contribute to the story refinement and delivery of data requirements through the delivery life cycle. Leverage architecture components in solution development, codes solutions to integrate, clean, transform, and control data in operational and analytical data systems per acceptance criteria. Build processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management and defining and building data pipelines and complex data sets to enable data-informed decision making, identifying and raising risks at all stages of the data engineering process. Develop and execute test plans to produce quantitative results, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and triages underlying causes. Drive complex information technology projects to ensure on-time delivery and adhering to team delivery and release processes. Identify, define, and document data engineering requirements, communicating required information for deployment, maintenance, support, and business functionality. Work with technology partners and a diverse set of stakeholders to identify and close gaps in data management standards adherence, negotiates paths forward, and helps identify and communicate solutions to complex data problems leveraging knowledge of information systems, techniques, and processes. Remote work may be permitted within a commutable distance from the worksite.

Requirements

Bachelor's degree or equivalent in Computer Science, Computer Information Systems, Management Information Systems, Engineering (any), or related: and 4 years of experience in the job offered or a related IT occupation.
Must include 4 years of experience in each of the following: Designing and implementing complex data integration pipelines utilizing Apache Camel Enterprise integration patterns, Spring Batch Framework, Logstash and Python Libraries; Developing custom web scraping solutions using advanced frameworks including Nutch crawlers and Scrapy with custom implementations to handle JavaScript rendered content; Architecting and deploying enterprise-grade RAG systems utilizing vector databases, implementing custom embedding models with sentence transformers, Hugging Face Transformers library and LangChain orchestration; Engineering Semantic Search using various search tools and models for dense vector embeddings to develop hybrid search and enable intelligent document retrieval and AI-Powered question answering in enterprise environments; Implementing comprehensive real time monitoring solutions using APM, data shippers, Beats, for system monitoring, performance metric collection and automated alerting mechanisms using Elastic Observability tools; and, Architecting, designing, developing and leveraging reusable architecture components and opensource frameworks in solution development while optimizing solutions to integrate, clean, transform, and control in large scale operational and analytical data systems.

Responsibilities

Develop and deliver data solutions to accomplish technology and business goals and initiatives.
Perform code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems.
Work with stakeholders and Product and Software Engineering teams to aid with implementing data requirements, analyzing performance, and researching and troubleshooting data problems within system engineering domains.
Work across development teams to contribute to the story refinement and delivery of data requirements through the delivery life cycle.
Leverage architecture components in solution development, codes solutions to integrate, clean, transform, and control data in operational and analytical data systems per acceptance criteria.
Build processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management and defining and building data pipelines and complex data sets to enable data-informed decision making, identifying and raising risks at all stages of the data engineering process.
Develop and execute test plans to produce quantitative results, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and triages underlying causes.
Drive complex information technology projects to ensure on-time delivery and adhering to team delivery and release processes.
Identify, define, and document data engineering requirements, communicating required information for deployment, maintenance, support, and business functionality.
Work with technology partners and a diverse set of stakeholders to identify and close gaps in data management standards adherence, negotiates paths forward, and helps identify and communicate solutions to complex data problems leveraging knowledge of information systems, techniques, and processes.