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Data Analyst Python Sql Jobs in Ogden, UT (NOW HIRING)

TAB Bank

Model Risk Management Analyst

Ogden, UT · On-site

Ability to program and conduct analysis using SQL, R, Python, SAS or similar applications * Familiarity with relational databases. * Experience with data visualization tools such as Tableau, Power BI ...

TAB Bank

Model Risk Management Analyst

Ogden, UT · On-site

Ability to program and conduct analysis using SQL, R, Python, SAS or similar applications * Familiarity with relational databases. * Experience with data visualization tools such as Tableau, Power BI ...

ARUP Laboratories

Data Consultant II

Salt Lake City, UT · On-site

Performs complex data analyses on large data files containing clinical and financial data. Supports ... Relational databases in Microsoft SQL Server ETL processes with SSIS Tableau VBA, python, or other ...

ARUP

Data Consultant II

Salt Lake City, UT · On-site

Performs complex data analyses on large data files containing clinical and financial data. Supports ... Relational databases in Microsoft SQL Server ETL processes with SSIS Tableau VBA, python, or other ...

ARUP Laboratories

Data Consultant II

Salt Lake City, UT · On-site

Performs complex data analyses on large data files containing clinical and financial data. Supports ... Relational databases in Microsoft SQL Server ETL processes with SSIS Tableau VBA, python, or other ...

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All JobsData Analyst Python Sql JobsData Analyst Python Sql Jobs in Ogden, UT

Data Analyst Python Sql information

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$33.3K

$80.9K

$133.1K

How much do data analyst python sql jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data analyst python sql in Ogden, UT is $80,870.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,200.00 and $94,900.00 per year, depending on experience, location, and employer.

Is Python and SQL enough for a data analyst?

For a data analyst, proficiency in Python and SQL is fundamental for data manipulation, analysis, and querying databases. However, additional skills such as data visualization, statistical knowledge, and familiarity with tools like Excel or BI platforms are often required to perform comprehensive analysis and communicate insights effectively.

What jobs can you get with SQL and Python?

Data analysts, data scientists, and business intelligence analysts commonly use SQL and Python to extract, analyze, and visualize data. These skills are essential for roles involving data management, reporting, and automation, often requiring knowledge of databases, statistical analysis, and data visualization tools.

How does a Data Analyst using Python and SQL typically collaborate with other departments within an organization?

Data Analysts proficient in Python and SQL frequently work alongside teams such as marketing, product development, finance, and operations. They gather requirements from stakeholders, translate business questions into data queries, and present actionable insights through dashboards or reports. Regular meetings and clear communication are essential to ensure that data solutions align with business goals, and Data Analysts often act as a bridge between technical data teams and non-technical decision makers. This collaborative environment helps drive data-informed decisions across the organization.

What are Data Analyst Python SQL jobs?

Data Analyst Python SQL jobs involve analyzing and interpreting data to help organizations make informed business decisions. These professionals use Python for data manipulation, automation, and visualization, and SQL for querying and managing data stored in relational databases. Typical tasks include data cleaning, building reports, extracting insights, and creating dashboards. Data Analysts often collaborate with other teams to understand data requirements and communicate findings through presentations or visualizations. Proficiency in both Python and SQL is essential for efficiently handling large data sets and solving complex analytical problems.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst; many professionals successfully transition into the field at various ages. Skills in Python, SQL, and data visualization tools are more important, and continuous learning can help overcome any age-related concerns. Employers value experience and analytical ability regardless of age.

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

To thrive as a Data Analyst specializing in Python and SQL, you need strong analytical skills, statistical knowledge, and proficiency in data manipulation, typically supported by a relevant degree or certification. Expertise in Python for data analysis, SQL for database querying, and experience with visualization tools like Tableau or Power BI are commonly expected. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for interpreting data and presenting actionable insights. These skills help ensure accurate analysis, impactful reporting, and informed decision-making within organizations.

Can Python and SQL work together?

Data analysts often use Python and SQL together to efficiently extract, manipulate, and analyze data. Python libraries like pandas and SQL connectors enable seamless integration, allowing analysts to automate workflows and perform complex data processing tasks within a single environment.

What is the difference between Data Analyst Python Sql vs Data Scientist?

AspectData Analyst Python SqlData Scientist
Required SkillsExcel, SQL, Python basics, data visualizationAdvanced Python, machine learning, statistical modeling
Work EnvironmentBusiness intelligence, reporting, dashboardsPredictive modeling, research, complex data analysis
Industry UsageFinance, marketing, retail, healthcareTech, finance, research institutions, startups

While Data Analysts with Python and SQL focus on interpreting data, creating reports, and visualizations, Data Scientists build predictive models and perform advanced statistical analysis. Both roles require Python and SQL skills, but Data Scientists typically have a stronger background in statistics and machine learning, making their work more research-oriented.

What job categories do people searching Data Analyst Python Sql jobs in Ogden, UT look for? The top searched job categories for Data Analyst Python Sql jobs in Ogden, UT are:
What cities near Ogden, UT are hiring for Data Analyst Python Sql jobs? Cities near Ogden, UT with the most Data Analyst Python Sql job openings:
Data Analyst Python Sql jobs near you
Infographic showing various Data Analyst Python Sql job openings in Ogden, UT as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 81% Full Time, 11% Part Time, 1% Temporary, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $80,870 per year, or $38.9 per hour.
Portfolio Analyst (CECL)

Portfolio Analyst (CECL)

First Electronic Bank

Salt Lake City, UT • On-site

Full-time

Re-posted 5 days ago

Job description

Description:

At First Electronic Bank (FEB), we are driven by the purpose to make credit accessible to everyday Americans, and their businesses. Partnering with some of the most innovative FinTech companies in the nation, we offer a wide range of consumer and commercial credit products on a national basis. Offering revolving lines of credit, private-label credit cards, installment financing programs and more, FEB’s engages with strategic, collaborative partnerships, promoting services and products to provide the most beneficial consumer and commercial financing solutions.


The Portfolio Analyst (CECL) supports the organization’s Current Expected Credit Losses (CECL) modeling, reporting, and analysis. This role assists in collecting, validating, and analyzing loan portfolio data to support allowance calculations, risk assessments, regulatory reporting, and management presentations. The ideal candidate has strong analytical skills, attention to detail, and a desire to grow within credit risk and financial modeling.


What You'll Do:

  • CECL Data & Modeling Support
  • Assist with preparing and validating monthly/quarterly CECL dataset inputs, ensuring accuracy and completeness.
  • Support the execution of CECL models, including probability of default (PD), loss given default (LGD), and prepayment models.
  • WARM methodology and Static Pool/Vintage Loss analysis.
  • Help maintain model documentation and version control.
  • Analysis & Reporting
  • Assist in generating CECL allowance calculations and variance analyses.
  • Prepare supporting schedules, workpapers, and dashboards for internal stakeholders and auditors.
  • Identify trends in portfolio performance, credit quality, and model outputs.
  • Controls, Compliance & Audit Support
  • Support internal and external audit requests related to CECL processes and controls.
  • Ensure CECL processes align with regulatory guidance and internal policies.
  • Contribute to the enhancement of data quality procedures and risk controls.
  • Cross-Functional Collaboration
  • Partner with Credit, Finance, Accounting, and Data teams to gather required inputs and clarify assumptions.
  • Support ad hoc analysis and special projects related to credit risk, loan portfolio performance, or regulatory changes.


Requirements:

What We're Looking For:

  • Degree in Finance, Economics, Accounting, Mathematics, Statistics, Data Analytics, or related field.
  • Strong analytical and quantitative skills.
  • Previous experience with vended software, like Moody’s Portfolio Analyzer or Impairment Studio preferred.
  • Proficiency in Excel; basic familiarity with SQL, R, Python, and data visualization tools.
  • Ability to work with large datasets and identify discrepancies.
  • Strong organizational skills and attention to detail.

Preferred Qualifications

  • 5+ years of experience in financial services, banking, credit risk, accounting, or data analytics.
  • Exposure to CECL methodology, ALLL, or other credit modeling frameworks.
  • Experience with loan servicing or core banking systems.
  • Understanding of credit risk metrics and loan portfolio structures.


Key Competencies

  • Analytical thinking
  • Problem-solving
  • Data accuracy and precision
  • Ability to manage multiple priorities
  • Strong communication skills
  • Initiative and willingness to learn complex financial concepts