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Operational Data Analyst Jobs in Atlanta, GA (NOW HIRING)

Position Summary The Data Analyst supports the analysis, interpretation, and reporting of programmatic, financial, and operational data to enable effective oversight of Head Start grants and regional ...

Analyze financial and operational data to identify trends, forecast results, and provide actionable business insights. * Perform variance analysis and prepare monthly, quarterly, and annual financial ...

Senior Data Analyst

Atlanta, GA · On-site

$82K - $104K/yr

In-Person / Face to Face JOB SUMMARY Under broad supervision, performs complex administrative duties and statistical, financial, or operational data analysis and reporting in support of management ...

Under limited supervision, the Senior Oracle SQL Data Analyst develops, maintains, and supports SQL solutions for operational reporting, research, executive decision-making, legislative reporting ...

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Data Analyst

Atlanta, GA · On-site

$65K - $85K/yr

Identify trends, patterns, anomalies, and areas of risk or improvement related to program performance and operations. * Prepare high-quality analytical reports, summaries, and data tables to support ...

Research/Data Analyst Senior

Atlanta, GA · On-site

$82K - $104K/yr

Under broad supervision, performs complex administrative duties and statistical, financial, or operational data analysis and reporting in support of management decision making in the functional area.

Data Analyst

Atlanta, GA · On-site

$40/hr

This individual will partner with our client's operational team to translate business requests into ... Previous experience with analytics preferred * Experience with data visualization tools such as ...

Under limited supervision, the Senior Oracle SQL Data Analyst develops, maintains, and supports SQL solutions for operational reporting, research, executive decision-making, legislative reporting ...

... operational team to translate business requests into data driven results and recommendations ... Previous experience with analytics preferred Experience with data visualization tools such as ...

Experience aligning analytics outcomes with financial and operational performance metrics ... Enable you to deepen your expertise in data, analytics, and value strategy within a globally ...

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Experience aligning analytics outcomes with financial and operational performance metrics ... Enable you to deepen your expertise in data, analytics, and value strategy within a globally ...

Data Analyst

Atlanta, GA · On-site

$85K - $95K/yr

As a commercial Data Analyst at Impiricus, you will play a vital role in driving data-informed decision-making across our commercial operations. You will be responsible for analyzing campaign ...

Data Analyst

Atlanta, GA · On-site

$56K - $63K/yr

The Data Analyst is crucial in empowering Atlanta Mission's strategic decisions and designs across Development, Volunteer Services, Marketing, Human Resources, Operations, Finance, as well as Client ...

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Operational Data Analyst information

See Atlanta, GA salary details

$32.7K

$79.5K

$130.8K

How much do operational data analyst jobs pay per year?

As of Aug 10, 2026, the average yearly pay for operational data analyst in Atlanta, GA is $79,471.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,100.00 and $93,300.00 per year, depending on experience, location, and employer.

What is the difference between Operational Data Analyst vs Data Analyst?

AspectOperational Data AnalystData Analyst
Required CredentialsBachelor's in Data Science, Business, or related field; proficiency in SQL, Excel, and data visualization toolsBachelor's in Statistics, Mathematics, or related field; similar technical skills
Work EnvironmentFocus on operational data, process improvement, and real-time analytics within organizationsBroader data analysis across various projects, including market research and reporting
Employer & Industry UsageUsed in industries like manufacturing, logistics, and retail for operational insightsCommon across finance, marketing, healthcare, and other sectors for data-driven decision-making

Operational Data Analysts specialize in analyzing operational data to improve processes and efficiency, often working closely with operational teams. Data Analysts have a broader scope, working on various data projects across different departments. While both roles require similar skills and education, their focus areas and typical industries differ, making each role unique in its contribution to organizational success.

What does an operational data analyst do?

An operational data analyst collects, analyzes, and interprets data related to business operations to identify trends, improve processes, and support decision-making. They often use tools like Excel, SQL, and data visualization software to create reports and dashboards, ensuring operational efficiency and effectiveness.

What is the salary of an operational data analyst vs operations analyst?

Operational Data Analysts typically earn a median salary ranging from $60,000 to $80,000 annually, depending on experience and location. Operations Analysts often have similar salaries, generally between $55,000 and $75,000, with variations based on industry and company size. Both roles require strong analytical skills and proficiency with data tools like Excel, SQL, or Tableau.

What is an operational data analyst?

An Operational Data Analyst is a professional who collects, analyzes, and interprets data related to an organization's daily operations. Their main goal is to identify trends, inefficiencies, and opportunities for process improvement by working closely with operational teams. They use various data analysis tools and methods to create reports, dashboards, and actionable insights that support decision-making. Operational Data Analysts often collaborate with different departments to ensure data accuracy and optimize business performance.

Is an operational data analyst entry level?

An entry-level operational data analyst position typically requires minimal professional experience, often focusing on skills in data analysis tools like Excel, SQL, or Tableau. Many roles are suitable for recent graduates or those with 1-2 years of related experience, and some employers may offer on-the-job training or certifications to develop necessary skills.

What are some common challenges faced by operational data analysts when working with cross-functional teams?

Operational Data Analysts often work closely with departments such as operations, finance, and IT, each of which may have different data priorities and technical backgrounds. A common challenge is translating complex data findings into actionable insights for non-technical stakeholders while ensuring data integrity across systems. Effective communication and a collaborative approach are essential to align goals, clarify requirements, and ensure successful project outcomes.

What are the key skills and qualifications needed to thrive as an operational data analyst, and why are they important?

To thrive as an Operational Data Analyst, you need strong analytical abilities, statistical knowledge, and experience with data management, often supported by a degree in data science, statistics, or a related field. Proficiency in data analysis tools such as SQL, Excel, Python, and business intelligence platforms like Tableau or Power BI is typically required. Excellent problem-solving skills, attention to detail, and effective communication help analysts interpret complex information and share actionable insights with stakeholders. These skills are crucial for optimizing business processes, enabling data-driven decisions, and delivering measurable operational improvements.
What job categories do people searching Operational Data Analyst jobs in Atlanta, GA look for? The top searched job categories for Operational Data Analyst jobs in Atlanta, GA are:
Infographic showing various Operational Data Analyst job openings in Atlanta, GA as of August 2026, with employment types broken down into 88% Full Time, 3% Temporary, and 9% Contract. Highlights an 85% In-person, and 15% Remote job distribution, with an average salary of $79,471 per year, or $38.2 per hour.

Full-time

Re-posted 9 days ago


Job description

Overview:
Data Analyst: This role applies industry-leading methodologies for working with large datasets to extract meaningful business insight and creatively solve business problems. This role will apply advanced methods and algorithms for identifying trends, predicting outcomes, and alerting the business to potential issues. Additionally, the Data Analyst is expected to present insights and recommendations to non-technical audiences and explain the benefits and impacts of the recommended solutions.
This role will create analytical models and datasets while working with a Data Engineer to develop code for extracting data from source systems, which will include the Relational Enterprise Data Warehouse, Operational Data Store, and Could platforms. The ideal candidate will also be passionate about developing machine learning models using Azure Databricks and/or Azure ML Studio, or a comparable platform for operationalizing Machine Learning workloads. Multiple could platforms expertise is desired.
Responsibilities:
  • Engage with business partners and stakeholders to understand business problems and translate them into data analytics solutions.
  • Coordinate and collaborate with data engineering, analytic engineering, and other resources to achieve business goals.
  • contribute to the end-to-end development and deployment of predictive and prescriptive models.
  • Explore large datasets using modeling, analysis, and visualization techniques.
  • Communicate results, analyses, and methodologies to technical and non-technical senior level stakeholders.
  • Ability to mentor, coach, and lead others.
  • Contribute to and help build ML/AI vision to support business strategy.

Required Knowledge, Skills, Abilities (Qualifications):
  • Degree in Data Science, Machine Learning, Applied Mathematics/Statistics, or a related field.
  • 3 years of experience applying data science, AI/machine learning, or analytics techniques to business problems.
  • Experience with supervised and unsupervised machine modeling techniques, with a focus on time-series forecasting.
  • Experience solving real-world problems using programming languages such as SQL, Spark, and Python, and deploying solutions to enterprise systems in data engineering and data analytics.

Ability to work on data Engineering and bigdata programming tools and technologies such as pig, Hive, Hadoop
Skills:
SQL, Spark, and Python,AI,ML