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. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.

Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.

We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.

Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. 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.

Overview:

The Data Modeler role is critical in designing and implementing robust data warehousing solutions. In this role, candidate will collaborate closely with product managers, business stakeholders, and the development community to ensure data models meet business needs and support efficient data management. This role requires a blend of technical expertise in data modeling methodologies and communication skills to effectively translate complex concepts for both technical and non-technical audiences.

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
• Partner with product managers and business representatives to understand data requirements and translate them into comprehensive data models (conceptual, logical, and physical)
• Ensure data models adhere to industry standards and best practices, promoting data quality and minimizing redundancy
• Document, communicate, and centrally manage data models for efficient access and reference
• Design technical data solutions aligned with business needs, providing clear guidance to development teams
• Collaborate with technical teams to troubleshoot complex SQL queries within ETL processes
• Leverage Business Intelligence tools to visualize insights gleaned from data models
• Actively participate in discussions and meetings, effectively communicating technical concepts to audiences with varying technical backgrounds
• Collaborate with product managers and business stakeholders to gather and translate requirements into conceptual, logical, and physical data models
• Design scalable, high-performance data models to support enterprise data warehousing and analytics
• Ensure adherence to data modeling standards, governance, and best practices to maintain data quality and minimize redundancy
• Develop and maintain data model documentation and metadata for centralized access and reuse
• Partner with architects and development teams to deliver business-aligned technical data solutions
• Provide support to ETL/data engineering teams, including SQL troubleshooting and data issue resolution
• Enable reporting and analytics by supporting BI tools and data visualization needs
• Participate in agile ceremonies and design reviews to ensure alignment with delivery goals
• Communicate complex data concepts effectively to technical and non-technical stakeholders

Required Qualifications:

• 10+ years of experience with Data Engineering
• 3+ years hands on experience in Scala
• 3+ years of hands-on experience in Spark
• Expertise in data modeling methodologies (3NF, dimensional, data vault) for enterprise-level data stores
• Strong understanding of data architecture concepts (data warehouse, data mart, ODS, ETL, reporting, analytics)
• Experience with relational and NoSQL database design (SQL Server, Oracle, Object Storage, MongoDB, Elasticsearch, etc.)
• Proficiency in data analysis and modeling tools (Power Designer, Erwin, etc.)
• Hands-on experience with SQL and/or PL/SQL
• Experience with Business Intelligence tools (Power BI, Tableau, etc.)
• Excellent communication and interpersonal skills for seamless collaboration with diverse stakeholders.

Desired Qualifications:

• Knowledge of payments industry data standards (ISO 20022) and regulatory experience within payments domain
• Understanding of Apache Hadoop and the Hadoop ecosystem
• Familiarity with data Lakehouse data modeling skills

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
• Solution Delivery Process

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