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Bank of America

Runs a US consumer bank, brokerage and investment bank

Data/AI Product Owner

Technical Product ManagementConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 2 years of experience in data, analytics, product ownership, data governance, business analysis, technology delivery, architecture, or related disciplines.
  • Strong interest in data, analytics, artificial intelligence, machine learning, intelligent automation, and emerging technologies, with a passion for applying these capabilities to business problems and measurable value.
  • Understanding of core data management concepts, including data quality, metadata, lineage, governance, and data lifecycle management.
  • Exposure to modern data platforms, cloud technologies, data integration patterns, analytics solutions, or artificial intelligence-enabled capabilities.
  • Strong analytical and problem-solving skills, including the ability to identify opportunities for simplification, modernization, automation, and reuse.
  • Ability to translate business and technology requirements into practical delivery approaches and influence decisions across multiple stakeholders.
  • Communication, stakeholder management, facilitation, and presentation skills across business and technology teams.
  • Experience working in Agile delivery environments, including collaboration with Product Owners, Architects, Engineering teams, and Agile Release Trains.
  • Curiosity, learning agility, and willingness to continuously develop expertise in data, analytics, artificial intelligence, and emerging technologies.

Responsibilities

  • Define a multi-year data platform strategy and roadmap for cloud-native, Lakehouse, streaming/event-driven, and open table format capabilities, balancing short-term delivery with long-term modernization.
  • Convert architecture principles into actionable guidance for teams and ensure plans are cost-aware, feasible, and credible.
  • Monitor and assess new data and analytics technologies, including distributed query engines, graph databases, NoSQL, Oracle 23AI, and Lakehouse architectures.
  • Evaluate artificial intelligence and machine learning use cases for scalability, risk, and business value, and advise on platforms, MLOps, and integration patterns.
  • Sponsor proofs of concept with delivery teams and set success criteria and engineering standards.
  • Scale validated patterns into reusable accelerators and templates, and measure return on investment to guide prioritization.
  • Drive migration from legacy warehouses to cloud-ready Lakehouse platforms, including Databricks and Snowflake, with secure, cost-efficient services.
  • Collaborate with Platform ART, CTI, and System Teams to optimize performance, resilience, and cost through FinOps.
  • Provide expertise in relational and NoSQL databases, open table formats such as Iceberg and Delta Lake, streaming with Kafka, and event-driven architectures.
  • Define reusable patterns for batch, streaming, APIs, and data services, and advocate data mesh principles where suitable.
  • Align with enterprise data strategy, governance, and approved tools, including Collibra, SALT, and Informatica.
  • Embed responsible artificial intelligence, model risk controls, lineage standards, and regulatory compliance, including GDPR and conduct risk, in solutions.
  • Lead data literacy programs, training, and communities of practice to foster adoption of artificial intelligence and modern engineering.
  • Promote best practices for business intelligence tools including ThoughtSpot, MicroStrategy, and Tableau to accelerate insights.
  • Serve as a trusted advisor to business, technology, and compliance teams by communicating strategic impact and cost-benefit.
  • Partner with Product Owners and Agile Release Trains to integrate platform strategy, artificial intelligence innovation, and modernization into delivery workflows.
  • Generate the product vision and roadmap to align with the strategic direction of the business or technology domain.
  • Communicate the product vision and roadmap to stakeholders and the team.
  • Collaborate with stakeholders to understand their needs and problems.
  • Prioritize and create work for a team, collaborating with cross-functional teams.
  • Create, prioritize, and refine stories in the product backlog.
  • Review and accept stories and make decisions regarding scope and requirements.
  • Partner with the team to ensure optimal value is obtained through technology and business subject-matter expertise.

Desired Qualifications

  • Experience in banking, payments, treasury, financial services, or other regulated industries.
  • Experience with data product management, data strategy, governance, or enterprise architecture initiatives.
  • Exposure to artificial intelligence and machine learning, generative artificial intelligence, intelligent automation, knowledge management, or advanced analytics use cases.
  • Experience with modern platforms such as Databricks, Snowflake, Kafka, Starburst, ThoughtSpot, Tableau, MicroStrategy, Informatica, or similar technologies.
  • Experience with cloud platforms such as Azure, AWS, or GCP.
  • Relevant certifications in Agile, Data Management, Cloud, AI, Analytics, or Product Management.

About the Company

Bank of America

Runs a US consumer bank, brokerage and investment bank

Bank of America runs one of the largest US banks, serving consumers, small businesses, wealthy families, corporations and institutional investors. Alongside checking accounts, credit cards, mortgages and business loans, it owns the Merrill brokerage, a private bank for wealthy clients and a global investment bank that advises on deals and trades stocks and bonds. Customers reach it through thousands of branches and ATMs and its mobile banking app. It earns money mainly from the gap between what it charges on loans and pays on deposits, plus fees from advice, asset management, deal work and trading. It grew from a San Francisco bank founded in 1904 and is headquartered in Charlotte, North Carolina.

Company size
10,001+
Company stage
IPO
Headquarters
Charlotte, NC
Founded
1904

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