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Data Analyst Jobs in Meridian, ID (NOW HIRING)

Allied Business Solutions

Data Analyst

Boise, ID · On-site

The Data Analyst is the single point of accountability for the accuracy, integrity, and consistency of Allied Business Solutions' core business data across our ERP, CRM, and PSA platforms. This is a ...

Lamb Weston

Technology Data Analyst

Eagle, ID · On-site

Title: Technology Data Analyst Location: Eagle, ID Job Requisition ID: Req-270930 Time Type: Full time About Lamb Weston You've probably enjoyed our fries without even knowing it! As a leading ...

Lambweston

Technology Data Analyst

Eagle, ID · On-site

Title: Technology Data Analyst Location: Eagle, ID Job Requisition ID: Req-270930 Time Type: Full time About Lamb Weston You've probably enjoyed our fries without even knowing it! As a leading ...

Clearwater Analytics

Sr. Technical Data Analyst

Boise, ID · On-site

$81K - $103K/yr

Technical Data Analyst uses business intelligence and reporting expertise to build the dashboards and reports our clients and their end users rely on to report investment portfolio information to ...

H R PUNDITS INC

Data Analyst V

Boise, ID · Remote

$130K/yr

Data Analyst V Location: USA Remote Responsibilities * Work with large and complex datasets to solve challenging problems using various analytical and statistical approaches. * Synthesize and analyze ...

City of Boise, ID

Insight Analyst- Fire

Boise, ID · On-site

$68K - $80K/yr

In this role, you'll perform advanced spatial and data analysis to identify trends, model complex scenarios, and support strategic decision-making. From evaluating performance and emergency response ...

All JobsData Analyst JobsData Analyst Jobs in Meridian, ID

Data Analyst information

See Meridian, ID salary details

$32.1K

$77.9K

$128.2K

How much do data analyst jobs pay per year?

As of Aug 2, 2026, the average yearly pay for data analyst in Meridian, ID is $77,928.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,900.00 and $91,500.00 per year, depending on experience, location, and employer.

What is the difference between Data Analyst vs Data Scientist?

AspectData AnalystData Scientist
Required CredentialsBachelor's degree in statistics, mathematics, or related field; often certifications in data analysis toolsBachelor's or master's in computer science, statistics, or related; often advanced certifications or degrees
Work EnvironmentBusiness settings, focusing on data reporting and visualizationResearch and development environments, focusing on predictive modeling and complex algorithms
Employer & Industry UsageRetail, finance, healthcare, and marketing companiesTech firms, research institutions, and large enterprises

While both roles analyze data, Data Analysts primarily focus on interpreting existing data to generate reports and insights, whereas Data Scientists develop predictive models and advanced algorithms to forecast trends and solve complex problems.

What are some common challenges Data Analysts face when working with large datasets, and how are they typically addressed?

Data Analysts often encounter challenges such as data quality issues, missing or inconsistent values, and slow processing times when handling large datasets. These challenges are typically addressed by implementing data cleaning routines, using advanced data management tools, and leveraging programming languages like Python or R for efficient data manipulation. Collaboration with database administrators and IT teams is also common to ensure data integrity and optimize data storage solutions. Staying updated with best practices in data wrangling and visualization helps Data Analysts deliver accurate and actionable insights.

Is 40 too late for data science?

A Data Analyst role is accessible at any age, including 40, as skills in data analysis, programming, and tools like Excel, SQL, and Python are more important than age. Many professionals successfully transition into data science or analytics later in their careers by gaining relevant certifications and experience.

Will AI replace a data analyst?

AI tools can automate routine data processing and basic analysis tasks, but data analysts are essential for interpreting complex data, making strategic decisions, and providing context. The role of a data analyst involves skills like critical thinking, domain knowledge, and communication that AI cannot fully replicate. Therefore, AI is more likely to augment rather than replace data analysts.

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

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and experience with visualization platforms such as Tableau or Power BI are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts interpret data insights and present findings clearly to stakeholders. These skills are crucial for transforming raw data into actionable business insights that drive informed decision-making.

What Does a Data Analyst Job Do?

Data Analysts use a range of methods to chart, examine, and analyze data for their clients. As a Data Analyst, your job is to analyze a company’s data using a combination of mathematical inspection, transformation, and modeling techniques to simplify and condense it. You may also need to present your reports to stakeholders. Because companies often use the results of the data analysis to make business decisions, Data Analysts need to confirm the accuracy of the data.

What does a Data Analyst do?

A Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions. They use statistical tools and software to interpret data sets, identify trends, and create visual reports. Data Analysts often collaborate with other departments to provide actionable insights and support strategic planning. Their work helps organizations optimize operations, track performance, and solve business problems using data-driven approaches.

Is it hard to get a data analyst job?

Securing a data analyst position can be competitive, often requiring strong skills in data manipulation, statistical analysis, and proficiency with tools like Excel, SQL, or Python. Candidates with relevant education, certifications, and experience in data visualization and reporting tend to have better chances of obtaining such roles.

What job does a data analyst do?

A data analyst collects, processes, and analyzes data to help organizations make informed decisions. They use tools like Excel, SQL, and data visualization software to identify trends, create reports, and support strategic planning. Strong analytical skills and attention to detail are essential for this role.
More about Data Analyst jobs
What are the most commonly searched types of Data Analyst jobs in Meridian, ID? The most popular types of Data Analyst jobs in Meridian, ID are:
What are popular job titles related to Data Analyst jobs in Meridian, ID? For Data Analyst jobs in Meridian, ID, the most frequently searched job titles are:
What job categories do people searching Data Analyst jobs in Meridian, ID look for? The top searched job categories for Data Analyst jobs in Meridian, ID are:
What cities near Meridian, ID are hiring for Data Analyst jobs? Cities near Meridian, ID with the most Data Analyst job openings:
Data Analyst jobs near you
Infographic showing various Data Analyst job openings in Meridian, ID as of July 2026, with employment types broken down into 88% Full Time, and 12% Part Time. Highlights an 69% In-person, 10% Hybrid, and 21% Remote job distribution, with an average salary of $77,928 per year, or $37.5 per hour.

Data Analyst

Allied Business Solutions

Boise, ID • On-site

Other

Posted 14 days ago

Job description

The Data Analyst is the single point of accountability for the accuracy, integrity, and consistency of Allied Business Solutions' core business data across our ERP, CRM, and PSA platforms. This is a hands-on, technical role focused on keeping data clean, aligned, and trustworthy as it moves between systems — through disciplined data standards, active auditing, direct ownership of integrations and data synchronization, and targeted automation that eliminates manual entry and enforces quality. The Data Analyst ensures that every department works from a single, reliable source of truth, and provides reporting that turns well-governed data into usable insight for sales, service, and finance.


Key Responsibilities:


Cross-System Data Stewardship & Integrity

  • Serve as the single point of accountability for data accuracy, completeness, and consistency across the ERP, CRM, PSA, and related business systems.
  • Establish and enforce data standards, naming conventions, and entry rules so records remain consistent across systems and users.
  • Perform regular audits to identify and resolve errors, duplicates, gaps, and cross-system mismatches.
  • Own master and reference data (customers, products, pricing, equipment) so a single source of truth is reflected consistently everywhere it appears.
  • Maintain data dictionaries and documentation covering field definitions, ownership, and standards.

Data Integration & Synchronization

  • Own the flow and synchronization of data between the ERP, CRM, PSA, and other platforms, ensuring records stay aligned across all systems.
  • Write and maintain SQL queries to validate, extract, and reconcile data.
  • Build and maintain API-based integrations; troubleshoot sync failures and drive root-cause resolution with vendors or internal stakeholders.
  • Monitor integration health and proactively catch and correct data drift before it reaches downstream teams.

Automation for Data Quality & CRM Workflows

  • Design, build, and maintain automated routines that reduce manual entry and enforce data quality — deduplication, validation, reconciliation, and exception alerting.
  • Build and maintain CRM workflow automations that streamline sales and service processes and keep records current.
  • Document automations and adapt them as business needs evolve.

Product, Pricing & Proposal Data

  • Maintain accurate product records, configurations, and pricing across systems.
  • Keep proposal templates and pricing data current so quotes and proposals generate from clean, correct source data.

Lease & Asset Data Reconciliation

  • Maintain lease and asset records and reconcile them against related data across systems for consistency.
  • Monitor key dates — renewals, expirations, and term changes — and flag them to the appropriate stakeholders.

Reporting & Data Support

  • Generate routine and ad hoc reports to support the sales, service, and finance teams.
  • Support cross-departmental data requests and help translate data into usable insight.
  • Identify opportunities to improve data workflows, accuracy, and reporting efficiency.


Qualifications:


Required

  • Associate's or Bachelor's degree in Information Systems, Computer Science, Business, or a related field, or equivalent relevant experience.
  • Proven experience managing data across CRM, ERP, PSA, or comparable business systems.
  • Hands-on SQL skills for querying, validation, and reconciliation.
  • Experience building and maintaining integrations (APIs) and troubleshooting data-sync issues.
  • Experience with process automation.
  • Strong attention to detail and a high standard for data accuracy.
  • Advanced proficiency in Microsoft Excel and comfort working with large datasets.
  • Strong organizational skills and the ability to manage multiple priorities.

Preferred

  • Familiarity with data governance and master data management practices.
  • Experience with data reporting and visualization/dashboarding tools.
  • Familiarity with lease or asset tracking systems.
  • Scripting for automation (e.g., Python or PowerShell) or experience with low-code automation platforms.
  • Background in the managed IT, technology, or copier/print industry.

Competencies

  • Ownership and accountability for data integrity
  • Problem-solving and analytical thinking
  • Technical aptitude and adaptability
  • Clear written and verbal communication
  • Dependability and follow-through
  • Collaboration across teams


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