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Bank Data Analytics Jobs in Utah (NOW HIRING)

Data Analytics Engineer

Ogden, UT ยท On-site

$112K - $134K/yr

Data Analyst Engineer to design, develop, and maintain scalable data solutions that support the bank's Business Intelligence pipelines, modeling, and reporting. This role bridges data engineering ...

... Data Analytics team at TAB Bank in Ogden, UT. The primary function of this role will be to support the Bank's strategic partner program by conducting reviews of the statistical/machine learning ...

... Data Analytics team at TAB Bank in Ogden, UT. The primary function of this role will be to support the Bank's strategic partner program by conducting reviews of the statistical/machine learning ...

The SVP, Consumer Bank Analytics is responsible for leading the analytics data strategy and insight generation across the Consumer Bank. This role serves as a strategic partner to Finance & Treasury ...

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Bank Data Analytics information

Do banks use data analysts?

Yes, banks employ data analysts to interpret financial data, assess risk, detect fraud, and support decision-making. These professionals often use tools like SQL, Excel, and data visualization software to analyze large datasets and improve banking operations.

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

Bank Data Analytics professionals work closely with various departments such as risk management, marketing, compliance, and IT. They translate complex data sets into actionable insights, guiding strategic decisions and helping teams understand customer behavior, detect fraud, and ensure regulatory compliance. Regular cross-functional meetings and project-based collaborations are common, allowing analytics professionals to align data-driven recommendations with business goals and operational needs. This collaborative structure enhances communication, streamlines workflow, and maximizes the value of data across the organization.

What is bank data analytics?

Bank data analytics is the process of collecting, processing, and analyzing large volumes of data generated by banking transactions and operations. It helps banks gain insights into customer behavior, detect fraud, manage risks, and improve decision-making. By leveraging advanced analytical tools and techniques, banks can enhance customer experiences, increase efficiency, and develop data-driven strategies for growth. Bank data analytics professionals work with big data, machine learning, and statistical models to extract meaningful patterns and support business objectives.

What does a data analyst do in banking?

A data analyst in banking collects, processes, and analyzes financial data to identify trends, support decision-making, and improve operational efficiency. They often use tools like Excel, SQL, and data visualization software to interpret large datasets and generate reports for management and compliance purposes.

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

AspectBank Data AnalyticsBank Data Analyst
Required SkillsData analysis, statistical modeling, programming (SQL, Python)Data analysis, reporting, basic statistical skills
Work EnvironmentData teams, analytics departments within banksBank branches, finance departments, risk management teams
CertificationsData analytics certifications, SQL, Python coursesFinance or banking certifications, possibly data skills
Industry UsageFocus on developing analytics models and insightsFocus on interpreting data for decision-making

Bank Data Analytics involves advanced data modeling and technical skills to develop insights, while a Bank Data Analyst primarily interprets data to support banking operations. Both roles require analytical skills, but Bank Data Analytics is more technical and model-driven, whereas Bank Data Analyst focuses on reporting and data interpretation within banking environments.

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

To thrive as a Bank Data Analytics professional, you need strong analytical skills, proficiency in statistics, and a solid background in finance or economics, often supported by a relevant degree. Expertise in data analysis tools such as SQL, Python, R, and experience with business intelligence platforms like Tableau or Power BI, as well as knowledge of data governance frameworks, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication help translate complex data insights into actionable recommendations for stakeholders. These skills are crucial for driving data-informed decisions that enhance financial performance and risk management in the banking sector.

Can a data analyst work at a bank?

Yes, a data analyst can work at a bank, 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 concepts.

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.
What cities in Utah are hiring for Bank Data Analytics jobs? Cities in Utah with the most Bank Data Analytics job openings:
Data Analytics Engineer

Data Analytics Engineer

TAB Bank

Ogden, UT โ€ข On-site

$112K - $134K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 26 days ago


Job description

Data Analyst Engineer to design, develop, and maintain scalable data solutions that support the bankโ€™s Business Intelligence pipelines, modeling, and reporting. This role bridges data engineering, analytics, and business intelligence by transforming complex data into reliable, actionable intelligence and insights for strategic decision-making across the organization. The ideal candidate combines strong analytical skills with technical expertise in SQL, data modeling, Python pipelines, and visualization tools.

Essential Duties and Responsibilities:

  • Collect, clean, and analyze large datasets from multiple sources
  • Design and maintain data models, dashboards, and reporting systems
  • Develop and optimize SQL queries, ETL processes, and data pipelines
  • Collaborate with business stakeholders to understand reporting and analytics needs
  • Monitor data quality, integrity, and consistency across systems
  • Build automated reports and visualizations using BI tools
  • Identify trends, patterns, and opportunities through statistical analysis
  • Support decision-making with data-driven recommendations
  • Work with data engineers and software teams to improve data architecture
  • Document data definitions, workflows, and technical processes

Required education and experience:

Bachelorโ€™s degree in Computer Science, Information Systems, Data Analytics, Statistics, or related field

  • 3+ years of experience in business intelligence, analytics engineering, or data engineering
  • Advanced SQL skills and experience working with large relational and cloud-based datasets
  • Proficiency in Python or another analytics/programming language
  • Understanding of data warehousing and data modeling concepts, including dimensional and normalized models
  • Experience with BI and visualization tools such as Power BI or Tableau
  • Strong analytical, communication, and problem-solving skills
  • Or an equivalent combination of education and experience that provides the required knowledge, skills, and abilities

Preferred education and experience:

ย MSSQL and Python experience preferred

  • Experience with large scale streaming pipelines is a plus
  • Snowflake experience is a plus
  • Financial Services and Commercial Banking experience is a plus

Competencies:

ย Proficient in Python and SQL

  • Data warehousing and modeling, including dimensional and normalized models
  • Tableau or Power BI
  • Must have independent problem-solving skills and ability to develop solutions to complex analytical/data modeling problems
  • Excellent verbal and written communication skills and the ability to interact professionally with a diverse group including executives, managers, and subject matter experts
  • Successfully engage in multiple initiatives simultaneously
  • Work successfully in a team environment using Agile Scrum methodologies
  • Willing to suggest improvements along with offering possible solutions

TAB Bank Offers:

  • Onsite Gym
  • Tuition Reimbursement
  • Paid Holidays
  • Gym Reimbursement
  • College Scholarships for Employees and Families
  • 401(k)
  • Paid Time Off (PTO)
  • Employee Assistance Program (EAP)
  • I Made the Grade
  • Holiday Club Program
  • Medical, Dental, Vision, Life and AD&D, Voluntary Disability, Flex Spending & Dependent Care

TAB Bank will not sponsor applicants for work visas.