Senior Data Engineer – AI-Ready Data & Platform Lead

Bank of America; Plano (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Bank of America is seeking a senior Data Engineer to lead design, governance, and continuous improvement of data and knowledge foundations supporting AI and agentic capabilities across Network Services. The role spans structured and unstructured sources, ensuring information is defined, organized, and ready for trusted AI consumption.

You will partner with product and domain experts to translate data into reusable AI-ready assets, aligning standards, guardrails, and scalable control frameworks

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, or related field.
• 7+ years of experience in data engineering, with demonstrated leadership in enterprise data platforms.
• Advanced proficiency in SQL and Python.
• Deep expertise in data integration, pipeline development, and large-scale data processing
• Strong experience implementing data quality frameworks and automated validation
• Advanced knowledge of data modeling, metadata, and lifecycle management
• Experience with data governance, lineage, and control frameworks
• Strong understanding of AI/ML data requirements and data readiness practices
• Proven ability to design solutions for scalable, high-performance analytics platforms

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
• Lead the design and improvement of data and knowledge assets that support AI and agentic use-cases across Network Services, including both structured and unstructured sources.
• Define and maintain standards for how documentation, configurations, telemetry, metadata, policies, standards, and operational knowledge should be organized, governed, and prepared for AI consumption.
• Partner with product and service subject matter experts to understand network technologies, operational context, and domain-specific knowledge required to improve model grounding and decision quality.
• Design and guide scalable methods for storing, governing, indexing, validating, and retrieving context assets needed for AI-enabled workflows and solutions.
• Establish and evolve preventative and detective controls that identify and reduce data quality, metadata quality, knowledge quality, lineage, and freshness issues before they affect downstream AI use.
• Define expectations for ownership, stewardship, lineage, freshness, governance, and control accountability across relevant data and knowledge domains.
• Build or guide the development of pipelines, transformations, validation routines, metadata structures, and supporting services that improve the quality and accessibility of AI-relevant context assets.

Skills

Analytical Thinking

Application Development

Data Management

Risk Management

Solution Design

Agile Practices

Architecture

Collaboration

Decision Making

DevOps Practices

Data Quality Management

Python

SQL

Critical Thinking

Education

Bachelor's degree in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, or related field

Master's degree in a technical or data-related field is a plus

Job description

Bank of America is seeking a senior Data Engineer to lead design, governance, and continuous improvement of data and knowledge foundations supporting AI and agentic capabilities across Network Services. The role spans structured and unstructured sources, ensuring information is defined, organized, and ready for trusted AI consumption.

You will partner with product and domain experts to translate data into reusable AI-ready assets, aligning standards, guardrails, and scalable control frameworks