Senior Data Engineer-AI/BI Analytics

Bank of America

Addison (TX)

On-site

USD 150,000 - 210,000

Full time

5 days ago

Be an early applicant

Get more replies from employers

Send a job-specific resume in minutes.

Job summary

Bank of America is seeking a senior leader to shape GenAI data governance and enterprise data platform strategy. You will define governance standards, metadata, data lineage, and adoption programs across multiple tenants.

You will partner with engineering, risk, and business stakeholders to drive scalable, secure, compliant data solutions and foster platform adoption. This role emphasizes hands-on execution and strategic thinking to deliver business value and trusted data for AI initiatives.

Qualifications

10+ years leading data management, data analytics, data governance, or data platform initiatives enabling AI or GenAI.
Deep expertise in data governance, metadata management, data lineage, business glossaries, data quality, MDM, and lifecycle management.
Strong experience implementing governance controls supporting privacy, security, risk, and regulatory compliance requirements.
Proven success driving enterprise adoption of data platforms, self-service analytics, cloud data services, and AI-enabled solutions.
Hands-on experience with metadata and governance platforms, including data catalogs, lineage tools, semantic layers, knowledge graphs, and business metadata repositories.
Experience establishing operating models for platform onboarding, tenant enablement, customer success, and service delivery.
Strong understanding of modern cloud-based data platforms and large-scale enterprise data ecosystems.
Experience managing multiple business tenants in shared enterprise platforms while ensuring governance, security, and operational controls.
Ability to define and monitor platform adoption metrics, governance KPIs, service health metrics, and operational effectiveness measures.
Excellent stakeholder management, communication, and influencing skills with senior business and technology leadership.
Demonstrated ability to balance strategic planning with hands-on execution in a complex enterprise environment.

Responsibilities

Assemble large, complex data sets meeting functional and non-functional requirements across multiple systems.
Maintain, clean, and manipulate large data for operational and analytics data systems; build data transformation pipelines and data quality controls.
Collaborate with development teams to understand data requirements and ensure feasible data architecture.
Define and build data pipelines enabling data-informed decision making with proper release and risk management.
Contribute to tests including integration, regression, and performance; lead triage of issues.
Identify gaps in data management standards and develop remediation plans; prototype toolsets.
Mentor Data Engineers in CI/CD delivery and define KPIs and controls.
Define and execute strategic roadmaps for governance, adoption, and tenant service capabilities.
Partner with engineering to ensure scalable, secure platform services; establish operating models and SLAs.
Evaluate emerging technologies related to governance, cataloging, metadata management, and AI governance.
Mentor and coach team members to foster governance, accountability, innovation, and customer-focused delivery.
Lead implementation and continuous improvement of enterprise data governance frameworks and operating models.
Drive adoption of metadata management, data lineage, glossaries, classification, and quality indicators across the enterprise.
Partner with data stewards and risk partners to ensure governance and regulatory compliance.
Enable discovery, understanding, and consumption of enterprise data assets via governance-enabled self-service capabilities.
Promote consistent use of lineage, tagging, and data quality indicators to improve trust.
Develop strategies to increase adoption of enterprise data platform capabilities, self-service analytics, and AI-enabled data solutions.
Define onboarding frameworks, playbooks, and training for tenant success and platform utilization.
Collaborate with business and technology stakeholders to improve platform capabilities and accessibility.
Drive awareness and education programs on platform services and governance requirements.
Measure adoption trends, identify barriers, and implement continuous improvement to maximize business value.

Skills

Analytical Thinking

Application Development

Data Management

Risk Management

Solution Design

Agile Practices

Architecture

Collaboration

Decision Making

DevOps Practices

Business Acumen

Data Quality Management

Financial Management

Solution Delivery Process

Test Engineering

Job description

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!

Position Summary

Join a groundbreaking team at Bank of America, at the forefront of innovation in AI. We are building the next generation of Gen AI platform, empowering new AI initiatives across Consumer, Small Business, Global Banking, and Wealth organizations. This is a unique opportunity to contribute to a critical platform that will enable secure, scalable, and high-performance AI capabilities across the organization. We value curiosity, collaboration, and a passion for pushing the boundaries of what's possible with AI.

This position is focused on design, build, and serve the Gen AI BI capabilities.

his is a unique opportunity to shape the enterprise data ecosystem by establishing governance standards, improving data discoverability, enabling self-service capabilities, supporting platform tenants, and ensuring secure, scalable, and compliant usage of data platform technologies. The ideal candidate combines deep expertise in data governance and metadata management with a strong customer-centric mindset focused on platform adoption and business value realization.

This role is responsible for defining and leading the governance, adoption, onboarding, and tenant support strategy for enterprise data platforms while partnering with engineering, architecture, risk, and business stakeholders to drive enterprise-wide outcomes. This job is responsible for driving data engineering efforts to deliver enterprise-wide capabilities and complex data solutions. Key responsibilities include directing code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems and working with the Project Management team to define outcomes and inform work structures. Job expectations include providing technical thought leadership by implementing complex data solutions and interactions across multiple systems and domains.

Responsibilities

Assembles large, complex data sets that meet functional and non-functional requirements, ensuring that the design and engineering approach is consistent across multiple systems
Maintains, improves, cleans, and manipulates large data for operational and analytics data systems, builds complex processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, and communicates required information for deployment, maintenance, and support of business functionality
Utilizes multiple architectural components in the design and development of client requirements and collaborates with development teams to understand data requirements and ensure the data architecture is feasible to implement
Defines and builds data pipelines to enable data-informed decision making, ensuring adherence to release processes and risk management routines
Contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies any test issues and errors, and leads triage of underlying causes
Leads the identification of gaps in data management standards adherence and works with appropriate partners to develop plans to close gaps, leading concept testing and conducting research to prototype toolsets and improve existing processes
Mentors Data Engineers in the delivery and release of continuous integration and continuous delivery events and defines key performance indicators and internal controls
Define and execute strategic roadmaps for governance, adoption, and tenant service capabilities.
Partner with engineering organizations to ensure platform services are scalable, secure, reliable, and aligned with enterprise standards.
Establish operating models, service processes, SLAs, and support frameworks that improve platform stability and user experience.
Evaluate emerging technologies and industry best practices related to data governance, cataloging, metadata management, platform operations, and AI governance.
Mentor and coach team members while fostering a culture of governance, accountability, innovation, and customer-focused delivery.
Lead the implementation and continuous improvement of enterprise data governance frameworks, standards, controls, and operating models.
Drive adoption of metadata management, data lineage, business glossaries, data classification, and data quality practices across the enterprise.
Partner with data stewards, platform teams, architects, and risk partners to ensure compliance with governance, privacy, security, and regulatory requirements.
Identify governance gaps and establish remediation plans to improve data quality, transparency, accountability, and trust.
Enable effective discovery, understanding, and consumption of enterprise data assets through governance-enabled self-service capabilities.
Promote consistent use of lineage, classification, tagging, annotations, and data quality indicators to improve trust and usability.
Develop and execute strategies to increase adoption of enterprise data platform capabilities, self-service analytics, and AI-enabled data solutions.
Define onboarding frameworks, best practices, playbooks, and training programs to accelerate tenant success and platform utilization.
Partner with business and technology stakeholders to understand user needs and improve platform capabilities, experience, and accessibility.
Drive awareness and education programs to increase understanding of platform services, governance requirements, and supported use cases.
Measure adoption trends, identify barriers, and implement continuous improvement initiatives to maximize business value.

Required qualifications

10+ years of experience leading data management, data analytics, data engineering, data governance, or data platform initiatives enabling AI, or GenAI.
Deep expertise in data governance, metadata management, data lineage, business glossaries, data quality, master data management, and information lifecycle management.
Strong experience implementing governance controls supporting privacy, security, risk, and regulatory compliance requirements.
Proven success driving enterprise adoption of data platforms, self-service analytics, cloud data services, and AI-enabled solutions.
Hands-on experience with metadata and governance platforms, including data catalogs, lineage tools, semantic layers, knowledge graphs, and business metadata repositories.
Experience establishing operating models for platform onboarding, tenant enablement, customer success, and service delivery.
Strong understanding of modern cloud-based data platforms and large-scale enterprise data ecosystems.
Experience managing multiple business tenants in shared enterprise platforms while ensuring appropriate governance, security, and operational controls.
Ability to define and monitor platform adoption metrics, governance KPIs, service health metrics, and operational effectiveness measures.
Excellent stakeholder management, communication, and influencing skills with senior business and technology leadership.
Demonstrated ability to balance strategic planning with hands‑on execution in a complex enterprise environment.

Desired Qualifications

Experience supporting enterprise AI, analytics, or data science platforms from a governance and enablement perspective.
Knowledge of data governance frameworks, AI governance, responsible AI, and model lifecycle governance.
Experience leading cloud migration, platform modernization, and adoption programs.
Strong understanding of user experience and customer journey design for enterprise data platforms.
Experience developing training, enablement, and community engagement programs to drive sustained platform adoption.
Track record of building high‑performing teams and driving a culture of quality, innovation, accountability, and continuous improvement.
Experience evaluating and piloting emerging governance, cataloging, observability, and platform management technologies.

Skills