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Financial Data Analyst Intern Jobs in Portland, OR

Role Overview This position is for a lead data analyst with a background in Payroll. The role ... layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K ...

Partner collaboratively with Global Support, Renewals, and Customer Success leaders to deliver data ... FP&A or corporate finance experience. * Strong foundational modeling skills in Excel and Google ...

Financial Analyst

Portland, OR ยท On-site

$26.50 - $31.25/hr

Assists with budgeting, forecasting, financial reporting, and data analysis while working closely with management, clients, and team members to support informed business decisions. Duties * Interface ...

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Financial Data Analyst Intern information

See Portland, OR salary details

$12

$23

$44

How much do financial data analyst intern jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for financial data analyst intern in Portland, OR is $23.87, according to ZipRecruiter salary data. Most workers in this role earn between $18.37 and $26.01 per hour, depending on experience, location, and employer.

What does a financial data analyst intern do?

A Financial Data Analyst Intern supports finance teams by collecting, analyzing, and interpreting financial data to help inform business decisions. Their tasks often include building spreadsheets, preparing reports, identifying trends, and assisting with forecasting and budgeting activities. Interns work with large datasets, use tools like Excel or SQL, and may also learn visualization software to present findings. The role provides hands-on experience in financial modeling, data analysis, and industry research, helping interns develop valuable analytical and technical skills.

What types of projects and tasks can a financial data analyst intern expect to work on during their internship?

As a Financial Data Analyst Intern, you can expect to support senior analysts and finance teams by gathering, cleaning, and analyzing large sets of financial data. Common tasks include building and maintaining financial models, preparing reports and dashboards, and assisting with forecasting and budgeting processes. Interns often collaborate with other departments, such as accounting or business operations, to ensure data accuracy and gain insights for decision-making. This hands-on experience helps interns develop technical and analytical skills while learning industry-standard tools and best practices.

What are the key skills and qualifications needed to thrive as a financial data analyst intern, and why are they important?

To thrive as a Financial Data Analyst Intern, you generally need strong quantitative skills, proficiency in data analysis, and a background in finance, accounting, or a related field. Familiarity with Excel, SQL, and data visualization tools like Tableau, as well as experience with financial modeling, are commonly required. Attention to detail, analytical thinking, and effective communication help interns interpret data accurately and present insights clearly. These skills are crucial for supporting data-driven decision-making and providing valuable financial insights to the organization.

What are the most commonly searched types of Financial Data Analyst jobs in Portland, OR?

The most popular types of Financial Data Analyst jobs in Portland, OR are:

What job categories do people searching Financial Data Analyst Intern jobs in Portland, OR look for?

The top searched job categories for Financial Data Analyst Intern jobs in Portland, OR are:

What cities near Portland, OR are hiring for Financial Data Analyst Intern jobs?

Cities near Portland, OR with the most Financial Data Analyst Intern job openings:

Infographic showing various Financial Data Analyst Intern job openings in Portland, OR as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $49,641 per year, or $23.9 per hour.

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Re-posted 21 days ago


Job description


Responsibilities include:
1. Interpreting data, analyzing results using SQL, Excel, and basic statistical techniques
2. Performing data analyses, analyzing data collection systems and other methods that optimize efficiency and data quality
3. Acquiring data from primary or secondary data sources and maintaining databases
4. Collecting, organizing, and interpreting database metadata (i.e., data structures, data relationships, data element descriptions), and capturing this in our Enterprise Data Catalog.
5. Modelling data, including master data, reference data, and transactional data objects, attributes, and relationships
6. Assessing gaps and conflicts between data definitions across multiple software assets.
7. Creating database schemas from data models.
8. Writing SQL to analyze data and data structures in databases
9. Assessing data quality in assigned data domains.
10. Providing guidance on master data and reference data governance.
11. Assisting with curating the Enterprise Data Catalog to scan new databases, data pipelines, data object definitions, PowerBI reports, and related metadata.
Required Experience & Skills:
1. Strong communication skills including interviewing subject matter experts (business and technical) to capture requirements, and effective writing skills to convey technical options and recommendations, and to produce required documentation such as functional design specifications.
2. At least 5 years of experience working with data modeling tools such as Visio, ERWin, or equivalent.
3. SQL Server Management Studio (SSMS) to analyze data content, data structures, and stored procedures.
4. Data warehouse design including normalized structures for Operational Data Stores, and star schema structures for data marts.
5. On premise and Azure cloud databases including SQL Server and Synapse
Preferred Experience
1. Utility industry knowledge, especially gas utilities
2. Knowledge of typical data patterns for shared services domains such as Finance, Human Resources, and IT
3. Informatica data management tools (eg, Enterprise Data Catalog) including data profiling and data lineage analysis
4. Knowledge of CMDB data models
5. Data Governance principles and methods
6. Reference data management, especially using Informatica Reference360