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Bank Data Analyst Jobs (NOW HIRING)

Prophecy Technologies

Data Analyst

Mount Laurel, NJ · On-site

Not specified Job Summary We are seeking an experienced Data Analyst with strong banking domain expertise, deep knowledge of data governance and data quality, and hands-on experience with Informatica ...

1 point system

Data Analyst

Chicago, IL · On-site

... Bank's technology metrics portfolio • Develop and maintain automated processes for data ... hoc analysis and deep dives to address specific business questions and challenges as needed. • ...

City National Bank

Senior Data Analyst

Charlotte, NC · On-site

$84K - $106K/yr

City National Bank is a subsidiary of Royal Bank of Canada, focused on helping clients, colleagues, and communities flourish. The Senior Data Analyst will lead the end-to-end process for data ...

Prophecy Technologies

Data Analyst

Jersey City, NJ · On-site

This role offers an exciting opportunity to work on complex data analysis projects in the banking and financial services domain. Key Responsibilities: * Design and develop data analysis models using ...

Programmers.io

Data Analyst

Tampa, FL · On-site

Data Analyst with strong experience in Big Data, Cloud (AWS & GCP), and AI/ML-enabled data ... Banking & Financial Services * Insurance Education Requirements * Bachelor's/master's in computer ...

CGI Inc.

Data Analyst

Cleveland, OH · On-site

Data Analyst Category: Software Development/ Engineering Main location: United States, Ohio ... Candidate should have functional knowledge in Banking Domain. The ideal candidate will have a can ...

Needham Bank

IT Data Architect

Needham, MA

$116K - $163K/yr

Design mappings between core structures and the bank's data model. · Support AI and advanced analytics solutions bydefining reusable data services, semantic layers, and scalable patterns forbatch ...

IT CURA Inc.

Data Analyst

Pasadena, CA · On-site

Conduct data analysis, data integration, and data management * Identify and develop new data ... Experience in Finance or Accounting in the banking industry preferred. * Bachelor's Degree in ...

MetroSys

Data Analyst

Santa Barbara, CA · On-site

MetroSys is seeking a Data Analyst to support enterprise reporting and analytics initiatives for a ... Prior experience supporting analytics in banking, financial services, or a regulated industry.

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All JobsBank Data Analyst Jobs

Bank Data Analyst information

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$34K

$82.6K

$136K

How much do bank data analyst jobs pay per year?

As of Jun 18, 2026, the average yearly pay for bank data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

Can a data analyst work in banks?

Yes, a data analyst can work in banks, where they analyze financial data, customer information, and transaction patterns to support decision-making and risk management. Skills in SQL, Excel, and data visualization tools are commonly required, along with knowledge of banking regulations and financial products.

What does a banking data analyst do?

A banking data analyst collects, analyzes, and interprets financial data to help banks make informed decisions, improve operations, and manage risks. They use tools like Excel, SQL, and data visualization software to identify trends and support strategic planning. Strong analytical skills and knowledge of banking regulations are essential for this role.

What is the salary of data analyst in JP Morgan?

The salary of a data analyst at JP Morgan typically ranges from $60,000 to $90,000 annually, depending on experience, location, and education. Entry-level positions may start lower, while experienced analysts or those with specialized skills can earn higher compensation. Benefits often include bonuses, health insurance, and opportunities for professional development.

How does a Bank Data Analyst typically collaborate with other departments within a financial institution?

Bank Data Analysts frequently work alongside teams in risk management, compliance, marketing, and IT to ensure data-driven decisions are made across the institution. They help translate complex data findings into actionable insights for these departments, often participating in cross-functional meetings and projects. Effective communication and teamwork are essential, as analysts must understand the needs of different business units and present their analyses in a way that supports strategic objectives.

What is the difference between Bank Data Analyst vs Credit Analyst?

AspectBank Data AnalystCredit Analyst
Required CredentialsBachelor's in Finance, Economics, or related field; data analysis certificationsBachelor's in Finance, Economics, or related field; financial analysis certifications
Work EnvironmentBanking institutions, financial servicesBanking, lending institutions, credit departments
Employer & Industry UsageUsed for analyzing banking data, customer trends, risk assessmentUsed for evaluating creditworthiness, loan approvals, risk analysis

Both roles involve financial analysis within banking environments, but a Bank Data Analyst focuses on analyzing banking data and customer trends, while a Credit Analyst specializes in assessing credit risk and approving loans. They share similar credentials and work settings, making them closely related but distinct in their primary functions.

Is 40 too late for data science?

A career as a data analyst or data scientist can be pursued at age 40 or older, as many employers value experience, domain knowledge, and analytical skills. Transitioning into data science may require learning programming languages like Python or R, and gaining familiarity with tools such as SQL and machine learning algorithms, but age is generally not a barrier to entering the field.

What does a Bank Data Analyst do?

A Bank Data Analyst is responsible for collecting, processing, and analyzing financial data to help banks make informed business decisions. They use statistical tools and software to interpret data sets, identify trends, and generate reports for management. Their work supports areas such as risk management, customer analytics, regulatory compliance, and product development. By translating complex data into actionable insights, they play a crucial role in optimizing banking operations and strategies.

What are the key skills and qualifications needed to thrive as a Bank Data Analyst, and why are they important?

To thrive as a Bank Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree such as finance, economics, or data science. Familiarity with data analysis tools like SQL, Python, Excel, and business intelligence platforms, as well as certifications in data analytics, are commonly required. Attention to detail, problem-solving abilities, and effective communication skills set outstanding analysts apart. These skills and qualities are vital for interpreting complex financial data accurately and delivering actionable insights to drive informed decision-making in banking operations.
More about Bank Data Analyst jobs
What cities are hiring for Bank Data Analyst jobs? Cities with the most Bank Data Analyst job openings:
What states have the most Bank Data Analyst jobs? States with the most job openings for Bank Data Analyst jobs include:
What job categories do people searching Bank Data Analyst jobs look for? The top searched job categories for Bank Data Analyst jobs are:
Bank Data Analyst jobs near you
Infographic showing various Bank Data Analyst job openings in the United States as of June 2026, with employment types broken down into 79% Full Time, 19% Part Time, and 2% Temporary. Highlights an 95% Physical, 3% Hybrid, and 2% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Data Analyst

Prophecy Technologies

Mount Laurel, NJ • On-site

Full-time

Posted 5 days ago

Job description

Role Name:
Data Analyst
Location: Mt. Laurel, NJ
Experience: 8+ Years
Duration: Not specified
Job Summary
We are seeking an experienced Data Analyst with strong banking domain expertise, deep knowledge of data governance and data quality, and hands-on experience with Informatica PowerCenter and Databricks. The role focuses on end-to-end data analysis, ETL validation, documentation, stakeholder collaboration, and ensuring alignment with enterprise data governance standards across cloud and on-prem platforms.
Key Responsibilities
• Translate business needs into detailed functional and technical specifications for Informatica PowerCenter mappings, workflows, and transformations
• Validate ETL loads, troubleshoot data discrepancies, and work with technical teams to resolve issues
• Support development, testing, and implementation of Informatica PowerCenter jobs aligned with business rules and governance standards
• Perform end-to-end data analysis including source-to-target mapping, data profiling, and gap identification using Informatica and SQL
• Support ingestion and transformation of large datasets using Databricks (PySpark, SQL) and Informatica workflows
• Create comprehensive Incoming Data Collections (IDCs) for cloud ingestion, defining data sources, ingestion frequency, file formats, orchestration, and Azure target layers
• Maintain documentation including data dictionaries, metadata, requirements, and mappings
• Ensure adherence to data quality, data governance, lineage, and security standards
• Communicate project status, risks, and issues effectively to stakeholders
• Provide thought leadership and participate in knowledge sharing and mentoring activities
• Contribute to team development, cross-training, and continuous improvement initiatives
• Build and maintain strong relationships with internal and external stakeholders
• Promote a positive, inclusive, and collaborative work environment
• Act as a brand ambassador for the business function and the bank
Required Skills & Experience
• 8+ years of experience in the banking domain
• Strong expertise in data quality and data governance principles, metadata, lineage, and security standards
• Hands-on experience with Informatica PowerCenter (mappings, workflows, transformations)
• Strong SQL skills for data analysis and validation
• Experience with Databricks using PySpark and SQL
• Strong documentation skills including data dictionaries, metadata, and requirements
• Good understanding of data models, data product lifecycle, and enterprise data structures
• Proven stakeholder management and communication skills
Competencies
• Banking Domain Expertise
• Data Governance & Data Quality
• ETL & Data Integration
• Data Analysis & Documentation
• Stakeholder Management & Leadership

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