Senior Data Engineer: AI-Ready Data & Governance

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

Job summary

Bank of America is seeking a senior Data Engineer leader to drive enterprise data platforms, governance, and AI-ready data assets. You will guide cross-functional teams, design scalable data architectures, and ensure data quality and compliance across networks and services.

The role emphasizes collaboration with product teams, applying DataOps/MLOps practices, and delivering trusted data for AI-enabled workflows within Network Services.

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 leadership in enterprise data platforms.
• Advanced proficiency in SQL and Python.
• Experience with data governance, lineage, and control frameworks.
• Strong understanding of AI/ML data requirements and data readiness practices.

Responsibilities

• Assembles large, complex data sets meeting functional and non-functional requirements across systems.
• Maintains, cleans, and manipulates large data for operations and analytics, builds complex data pipelines.
• Collaborates with development teams to ensure data architecture feasibility.
• Defines and builds data pipelines enabling data-informed decisions and risk management.
• Contributes to test suites and leads triage of issues.
• Leads data governance initiatives and mentors engineers in CI/CD practices.

Skills

Analytical Thinking

Decision Making

Collaboration

Critical Thinking

Data Management

Architecture

DevOps Practices

Leadership

Agile Practices

Problem Solving

Education

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

Tools

SQL

Python

Job description

Bank of America is seeking a senior Data Engineer leader to drive enterprise data platforms, governance, and AI-ready data assets. You will guide cross-functional teams, design scalable data architectures, and ensure data quality and compliance across networks and services.

The role emphasizes collaboration with product teams, applying DataOps/MLOps practices, and delivering trusted data for AI-enabled workflows within Network Services.