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Full Stack Data Analyst Jobs in Georgia (NOW HIRING)

We are a venture-backed, fast-growing team where technology, data, and AI are core to how we ... The Role We are hiring a Full-Stack Engineer to own technically complex projects end-to-end within ...

We are a venture-backed, fast-growing team where technology, data, and AI are core to how we ... The Role We are hiring a Full-Stack Engineer to own technically complex projects end-to-end within ...

We are a venture-backed, fast-growing team where technology, data, and AI are core to how we ... The Role We are hiring a Full-Stack Developer to build internal tools, automations, and ...

We are a venture-backed, fast-growing team where technology, data, and AI are core to how we ... The Role We are hiring a Full-Stack Developer to build internal tools, automations, and ...

Java Full Stack Developer

Alpharetta, GA · On-site

$51.25 - $66.25/hr

... excellent analytical and problem solving skills that are coupled with strong communication ... Good knowledge of SQL with Database design and Data Modelling, creating Stored Procedure, Joins ...

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Showing results 1-20

Full Stack Data Analyst information

See Georgia salary details

$28.7K

$69.8K

$114.8K

How much do full stack data analyst jobs pay per year?

As of Jun 18, 2026, the average yearly pay for full stack data analyst in Georgia is $69,780.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,800.00 and $81,900.00 per year, depending on experience, location, and employer.

What is the difference between Full Stack Data Analyst vs Data Scientist?

AspectFull Stack Data AnalystData Scientist
Required SkillsData analysis, visualization, basic programming, SQL, reportingAdvanced programming, statistical modeling, machine learning, data engineering
Work EnvironmentBusiness teams, analytics departments, reporting toolsResearch teams, data science departments, AI/ML projects
CertificationsData analysis, SQL, Excel certificationsData science, machine learning, Python/R certifications
Industry UsageBusiness intelligence, marketing, financeResearch, AI development, predictive modeling

While both roles involve working with data, Full Stack Data Analysts focus on end-to-end data analysis and reporting within business contexts, whereas Data Scientists develop advanced models and algorithms for predictive insights. The roles often overlap in skills like SQL and programming, but Data Scientists typically require deeper expertise in statistical methods and machine learning.

What cities in Georgia are hiring for Full Stack Data Analyst jobs? Cities in Georgia with the most Full Stack Data Analyst job openings:
Infographic showing various Full Stack Data Analyst job openings in Georgia as of June 2026, with employment types broken down into 40% Full Time, 50% Part Time, and 10% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $69,780 per year, or $33.5 per hour.
Full-Stack Engineer

Full-Stack Engineer

Slip Robotics

Atlanta, GA • On-site

Full-time

Medical, Dental, Vision

Posted 2 days ago


Job description

Slip Robotics builds autonomous robotic systems for warehouse logistics. We are a venture-backed, fast-growing team where technology, data, and AI are core to how we operate - not just what we sell. Our Digital Solutions team builds the internal tools, workflow automations, enterprise integrations, and governed systems that keep the company scaling efficiently.
The Role
We are hiring a Full-Stack Engineer to own technically complex projects end-to-end within Slip's Digital Solutions function. This role carries a heavier emphasis on software architecture, system design, and production-grade engineering - you will design the systems that internal tools live inside, not just write features within them.
You will build deep context across Slip's data infrastructure and enterprise system landscape, and use that context to architect integration layers, internal applications, and platform components that are reliable, scalable, and maintainable.
AI is a daily accelerant. You will use AI tools for code generation, prototyping, testing, and integration work, and contribute to the team's shared development standards for AI-assisted engineering.
What You Will Do
  • Architect and implement internal applications, cross-system integrations, and workflow automations with a focus on scalability and reliability.
  • Build and maintain integration layers connecting enterprise systems (NetSuite, HubSpot, Propel PLM, and others) - APIs, data synchronization pipelines, and event-driven workflows.
  • Productionize prototypes and team-built utilities to production standards with proper error handling, monitoring, documentation, and automated testing.
  • Use AI-assisted development daily. Contribute to shared AI development standards and reusable components.
  • Support platform infrastructure, CI/CD pipelines, and deployment workflows. Ensure tools meet security and compliance requirements.
  • Serve as a technical resource across the organization - evaluate integration feasibility, advise teams on technical approaches, and contribute to architecture reviews.

Requirements
  • 5+ years of professional software engineering experience with strong full-stack capabilities (modern frontend, backend services, relational and document databases, REST/GraphQL APIs).
  • Demonstrated ability to architect systems end-to-end - not just write features, but design the structure that features live inside.
  • Experience building and maintaining enterprise integrations (ERP, CRM, or similar SaaS platform APIs).
  • Proficiency in at least two of: Python, TypeScript/Node.js, React. Experience with PostgreSQL and familiarity with DynamoDB or NoSQL databases.
  • Strong AI fluency - active use of AI coding assistants, LLM APIs, and AI-assisted development workflows as part of daily practice.
  • Experience with AWS, containerization, and CI/CD automation.
  • Production engineering mindset - monitoring, alerting, error handling, and documentation are not afterthoughts.
Bonus Points
  • Experience with data engineering tools (Snowflake, dbt, Airflow, or similar).
  • Background in robotics, logistics, manufacturing, or hardware companies.
  • Familiarity with SOC 2 compliance environments and secure development practices.
  • Experience contributing to shared SDKs, component libraries, or internal developer platforms.

Benefits
  • Competitive salary and equity in an early-stage robotics company
  • Comprehensive benefits including health, dental, and vision
  • Permissive time off policy