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Bank Data Processing Jobs (NOW HIRING)

Snowflake Data Engineer - DBT

Johnston, RI · On-site

$115K - $138K/yr

... banking and financial data initiatives. Key Responsibilities * Design, develop, and optimize ... Write highly optimized SQL for large-scale data processing. * Design and implement data warehouse ...

Experience in Banking, Regulatory, Data Warehouse/Data Lakes, AWS/ Snowflake * Understanding of data warehousing and transformation methods, lineage documentation, and ETL processes. * Knowledge of ...

Sr Data Analyst, Data Products

Raleigh, NC · On-site

$83K - $105K/yr

Experience in Banking, Regulatory, Data Warehouse/Data Lakes, AWS/ Snowflake * Understanding of data warehousing and transformation methods, lineage documentation, and ETL processes * Knowledge of ...

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Bank Data Processing information

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$12

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$34

How much do bank data processing jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for bank data processing in the United States is $20.27, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $22.36 per hour, depending on experience, location, and employer.

What is bank data processing?

Bank data processing refers to the collection, management, and analysis of financial data within a banking institution. This involves using specialized software and systems to process transactions, update account information, and generate financial reports. Bank data processing ensures the accuracy, security, and efficiency of handling large volumes of data related to customer accounts, loans, and payments. It is a critical function that supports daily banking operations and regulatory compliance.

What are the key skills and qualifications needed to thrive as a bank data processing specialist?

To thrive as a Bank Data Processing Specialist, you need strong analytical skills, attention to detail, and a background in finance or information technology, often supported by an associate degree or relevant experience. Familiarity with banking software systems, data entry platforms, and spreadsheet tools like Excel is typically required. Accuracy, reliability, and effective communication are important soft skills for managing sensitive financial data and collaborating with team members. These skills and qualities are crucial for ensuring data integrity, regulatory compliance, and efficient banking operations.

What are some common challenges faced in a bank data processing role, and how can I prepare for them?

In a Bank Data Processing role, you’ll often encounter challenges such as managing large volumes of financial transactions under tight deadlines, ensuring data accuracy, and adhering to strict regulatory requirements. To prepare, it’s helpful to develop strong attention to detail, time management skills, and a thorough understanding of banking software systems. Collaboration with other departments, such as compliance and IT, is also key to resolving discrepancies efficiently and maintaining seamless operations. Proactively seeking training in relevant data processing platforms and familiarizing yourself with industry regulations will help you succeed.

What is the difference between Bank Data Processing vs Bank Teller?

AspectBank Data ProcessingBank Teller
Required CredentialsHigh school diploma or equivalent; some roles may require data entry certificationsHigh school diploma or equivalent; customer service skills
Work EnvironmentOffice setting, data centers, or back-office operationsBank branch, customer service counters
Employer & Industry UsageFinancial institutions, data processing companiesRetail banks, credit unions, branches
Common Search & ComparisonData entry, processing, verificationCustomer transactions, account management

Bank Data Processing involves handling and verifying financial data in an office environment, focusing on accuracy and data management. In contrast, a Bank Teller interacts directly with customers, handling transactions and providing banking services at branch locations. While both roles are within the banking industry, they serve different functions and require different skill sets.

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What are popular job titles related to Bank Data Processing jobs?

For Bank Data Processing jobs, the most frequently searched job titles are:

Infographic showing various Bank Data Processing job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $42,153 per year, or $20.3 per hour.

Manager, Data Strategy and Governance Office

Arlington, VA • On-site

Other

Re-posted 6 days ago


Key responsibilities

  • Lead the development, execution, and continuous improvement of the Bank's enterprise data strategy and operating model.

  • Oversee the Bank's enterprise data governance and information management programs, including policies, standards, and compliance monitoring.

  • Manage the Bank's Data Product Owner function, ensuring data products deliver measurable business value and support strategic initiatives.


Job description

Head of Enterprise Data Strategy and Governance

Job Category: Banking

Requisition Number: HEADO001528

  • Posted : August 4, 2026
  • Full-Time
  • Hybrid
Locations

Showing 1 location

VA Office
2011 Crystal Drive
Suite 800
Arlington, VA 22932, USA

VA Office
2011 Crystal Drive
Suite 800
Arlington, VA 22932, USA

Role Description Summary
The Head of Enterprise Data Strategy and Governance leads the Bank's enterprise data and AI strategy, and oversees governance of data, context, and AI assets. While reporting to the CIO, responsibilities will include enterprise data and AI architecture, data product and quality management, enterprise content management, information lifecycle management, and AI data enablement programs. This leadership role establishes and executes a comprehensive strategy to ensure that data and information assets are trusted, governed, secure, accessible, and leveraged to support strategic growth, operational excellence, regulatory compliance, innovation, and informed decision-making.


This role serves as the Bank's leader for enterprise data management and governance practices, partnering closely with business and technology leaders to maximize the value of data and information assets. The position is responsible for defining the enterprise data vision, guiding modernization of the Bank's data ecosystem, advancing data products and analytics capabilities, enabling responsible AI adoption through effective data management practices, and ensuring alignment with business objectives, risk management standards, and regulatory expectations.


Role Responsibilities:


Enterprise Data Strategy and Leadership
• Accountable for developing, executing, measuring, and continuously evolving the Bank's enterprise data strategy and associated operating model.
• Establish goals, objectives, governance structures, key performance indicators, operating procedures, and communications frameworks for the Data Strategy and Governance Office (DSGO).
• Lead strategic and operational planning for enterprise data, information management, analytics, governance, and content management capabilities.
• Identify opportunities to leverage data and information assets to improve business performance, member experience, operational efficiency, and competitive positioning balanced with risk management effectiveness and compliance.
• Collaborate with business and technology leaders to prioritize enterprise data initiatives and investments and ROI.
• Develop a data portfolio of business cases, cost-benefit analyses, and investment recommendations related to enterprise data, analytics, information management, and modernization initiatives.
• Partner with the PMO to oversee the enterprise data portfolio, resource planning, prioritization, and execution of data-related initiatives.
• Lead management reviews and opportunity assessments focused on process efficiency, cost optimization, business growth, and innovation opportunities.


Data Governance and Information Management
• Lead the Bank's enterprise data governance and information management programs.
• Establish and maintain enterprise data policies, standards, controls, procedures, communications, and governance frameworks.
• Define and oversee processes for monitoring compliance with enterprise data policies and standards.
• Establish and report key performance indicators (KPIs) and key risk indicators (KRIs) related to data governance, data quality, and information management effectiveness.
• Collaborate with Information Security, Compliance, Enterprise Risk Management, Legal, and Internal Audit to ensure adherence to regulatory, privacy, security, and risk management requirements.
• Promote enterprise-wide adoption of governance standards and confidence in enterprise data assets, reports, dashboards, data products, and analytical solutions.
• Oversee enterprise reference data, master data, metadata management, business glossary, data stewardship, and data lineage programs.
• Lead the Enterprise Data Quality Program, including data quality standards, monitoring processes, issue remediation procedures, and reporting.
• Ensure trusted and reliable data is available to support operational, analytical, regulatory, and strategic decision-making.
• Oversee service level agreements (SLA), data contracts, operational metrics, and performance targets related to enterprise data services.
• Oversee the lifecycle management of enterprise information assets from creation through retention, archival, and disposition.


Data Product Management
• Lead and manage the Bank's Data Product Owner function.
• Establish and mature a data product operating model aligned with business priorities.
• Define success metrics and accountability measures for enterprise data products.
• Ensure enterprise data products deliver measurable business value and support strategic initiatives.
• Report on the performance of data product contracts for consumers and applications.
• Partner with business leaders to prioritize data product investments and enhancements.
• Promote adoption and utilization of enterprise data products and a data marketplace across the organization along with establish trust metrics.
Artificial Intelligence and Data Enablement
• Partner with business and technology leaders to identify opportunities and use cases supporting artificial intelligence, advanced analytics, automation, and decision intelligence initiatives.
• Ensure enterprise data assets are governed, documented, trusted, and managed to support AI and machine learning use cases.
• Establish data quality, metadata, lineage, semantics, context, and governance standards required to support responsible AI initiatives.
• Collaborate with the Bank's AI governance framework and stakeholders to ensure AI solutions are supported by appropriate data controls and oversight for transparency and explainability.
• Assess enterprise data readiness for AI initiatives and identify required improvements.
• Develop strategies to improve data accessibility and trust by enhancing data quality, usability, and availability for AI and advanced analytics applications.
• Monitor emerging trends in AI, analytics, and data management and recommend opportunities that align with the Bank's strategic objectives.
Enterprise Data Architecture and Modernization
• Define, maintain, and communicate the Bank's enterprise data architecture strategy and roadmap.
• Collaborate with Infrastructure and Application Development teams to establish target state and optimal integration architectures for enterprise data platforms, analytical environments, information repositories, metadata management, and integration capabilities.
• Lead strategic planning for modernization of the Enterprise Data Warehouse, data integration capabilities, semantic layers, and supporting data platforms.
• Establish enterprise standards for data models, data products, metadata structures, integration patterns, data lineage, and information architecture.
• Collaborate with Infrastructure, Application Development, and business stakeholders to ensure alignment between business requirements, data architecture, and technology capabilities to ensure SLAs, business continuity, and disaster recovery scenarios.
• Guide evaluation and selection of data management, integration, analytics, and governance technologies.
• Ensure enterprise data architecture supports regulatory reporting, operational reporting, analytics, data products, AI initiatives, and future business requirements.
• Establish governance requirements at every level for future-state data platforms and integration capabilities.
• Review and approve governance, metadata, data quality, and business readiness aspects of major platform releases and modernization initiatives.
• Monitor emerging industry trends and recommend improvements to the Bank's enterprise data ecosystem.
Enterprise Content Management (ECM)
• Lead the Bank's Enterprise Content Management strategy, roadmap, governance framework, and operating model.
• Oversee lifecycle management of unstructured information assets and content repositories.
• Ensure ECM solutions support information governance, records management, regulatory compliance, operational efficiency, and digital transformation initiatives.
• Establish standards for enterprise information classification, retention, archival, and disposition.
• Collaborate with business and technology teams to improve document management, workflow automation, information accessibility, and adherence to information lifecycle regulations.
• Support modernization of ECM capabilities and integration with enterprise information management practices.
Leadership and Talent Development
• Lead, mentor, develop, and manage DSGO personnel
• Provide leadership for Data Governance, Data Product Management, Data Quality, ECM, and related information management functions.
• Build organizational capabilities in governance, architecture, information management, analytics, and AI readiness.
• Develop succession plans and talent strategies to support future organizational needs.
• Champion enterprise data culture and community building through data literacy, education programs, and meetup events.
• Promote a culture of accountability, collaboration, innovation, continuous improvement, and business partnership.


Minimum Qualifications


Experience
• 10+ years of progressive leadership experience in data management, data governance, data architecture, analytics, information management, or related disciplines.
• 5+ years leading enterprise-scale data governance and data strategy programs.
• Demonstrated experience leading enterprise data modernization initiatives.
• Experience with enterprise data architecture, data warehousing, and data integration platforms.
• Experience supporting artificial intelligence, machine learning, advanced analytics, or automation initiatives.
• Experience leading data quality, information governance, or enterprise content management programs.
• Experience working within a regulated financial services environment.
• Experience presenting recommendations and strategy to executive leadership and governance committees.
Knowledge and Skills
• Enterprise Data Governance
• Data Management and DAMA DMBOK
• Data Product Management
• Data Quality Management
• Metadata Management
• Master and Reference Data Management
• Information Lifecycle Management
• Enterprise Content Management
• AI Data Governance and Responsible AI Principles
• Business Intelligence and Analytics
• Regulatory and Risk Management Practices
• Strategic Planning and Organizational Leadership
• Demonstrated ability to lead enterprise data architecture and modernization initiatives.


Education
Bachelor's degree in Computer Science, Information Systems, Data Management, Business Administration, or a related field.
Master's degree preferred.

Work Environment:
Hybrid – Employees will work from both remote and onsite locations. Employees must live within a reasonable commuting distance of the office and are required to be onsite at least two (2) days per week, specifically on Tuesdays and Wednesdays. Certain positions or business needs may require additional in-office days.

General Notice:
This position description describes the general nature and level of work performed by the employee assigned to this position and should not be interpreted as all inclusive. It does not state or imply that these are the only duties and responsibilities assigned to the position. The employee may be required to perform other job-related duties. All requirements are subject to change and to possible modification to reasonably accommodate individuals with a disability.

This position description does not constitute an employment agreement between the Bank and employee and is subject to change by the employer as the needs of the Bank and requirements of the position change.

AA/EOE

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EducationExperienceLicenses & Certifications

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.For further information, please review the Know Your Rights notice from the Department of Labor.

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