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Data Intelligence Jobs in Georgia (NOW HIRING)

Senior AI Data Engineer

Atlanta, GA ยท On-site

$121K - $151K/yr

Build the data intelligence foundation required for AI systems, including trusted context, business understanding, and reliable access to enterprise data. * Design architectures that enable AI ...

Senior AI Data Engineer

Atlanta, GA ยท On-site

$121K - $151K/yr

Build the data intelligence foundation required for AI systems, including trusted context, business understanding, and reliable access to enterprise data. * Design architectures that enable AI ...

Showing results 21-40

Data Intelligence information

See Georgia salary details

$67.1K

$112.1K

$150.7K

How much do data intelligence jobs pay per year?

As of Sep 5, 2026, the average yearly pay for data intelligence in Georgia is $112,061.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,600.00 and $123,700.00 per year, depending on experience, location, and employer.

What is a data intelligence?

A Data Intelligence job involves collecting, analyzing, and interpreting data to support decision-making and business strategy. Professionals in this field use various tools and techniques, including data mining, machine learning, and visualization, to uncover insights and trends. They work closely with stakeholders to translate data into actionable recommendations, improving efficiency and innovation. Roles may vary from data analysts to data scientists, depending on the organization's needs and complexity.

What are the typical daily responsibilities of a data intelligence professional?

A Data Intelligence professional typically spends their workday collecting, processing, and analyzing large datasets to uncover trends and actionable insights. They often collaborate with cross-functional teams, such as business analysts, product managers, or IT professionals, to define data requirements and support ongoing projects. Additional responsibilities may include creating dashboards or reports, ensuring data accuracy and integrity, and communicating findings to both technical and non-technical stakeholders. Frequent problem-solving, adapting to shifting priorities, and keeping up with the latest analytical tools are also common aspects of the role.

What are the key skills and qualifications needed to thrive in the data intelligence position, and why are they important?

To thrive in Data Intelligence, you need strong analytical skills, a solid understanding of data science principles, and a background in fields such as statistics, computer science, or information systems. Familiarity with tools like SQL, Python, Tableau, and experience with data warehousing and business intelligence platforms are highly valuable, as are certifications such as Certified Analytics Professional (CAP) or related credentials. Excellent problem-solving abilities, effective communication, and a collaborative mindset help drive actionable insights from complex datasets. These skills are essential for translating raw data into meaningful intelligence that guides business strategy and decision-making.

What cities in Georgia are hiring for Data Intelligence jobs?

Cities in Georgia with the most Data Intelligence job openings:

Infographic showing various Data Intelligence job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $112,061 per year, or $53.9 per hour.

Senior AI Data Engineer

Kiongroup

Atlanta, GA โ€ข On-site

$121K - $151K/yr

Full-time

Re-posted 15 days ago


Job description

We are seeking a highly experienced Senior AI Data Engineer to help transform our Enterprise Data Platform into an AI-native, intelligent platform where AI agents can discover, understand, and interact with enterprise data and platform capabilities.
This role focuses on building the foundations that enable AI agents and intelligent applications to effectively leverage enterprise data, including context engineering, semantic understanding, metadata intelligence, AI-ready data abstractions, and agent-driven platform capabilities.
This is a hands-on senior role requiring deep expertise in cloud data engineering, AI-enabled data platforms, agentic AI architectures, semantic modeling, metadata and context engineering, and modern software development practices. The ideal candidate combines strong technical execution skills with architectural thinking and the ability to design and deliver scalable AI capabilities that integrate seamlessly with enterprise data platforms and business workflows.We offer:
  • Career Development
  • Competitive Compensation and Benefits
  • Pay Transparency
  • Global Opportunities

Learn More Here:https://www.dematic.com/en-us/about/careers/what-we-offer

Dematic provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

The base pay range for this role is estimated to be $121,200.00 - $151,500.00 at the time of posting. Final compensation will be determined by various factors such as work location, education, experience, knowledge and skills.

Tasks and Qualifications:

This is What You Will do in This Role:

  • Evolve the Enterprise Data Platform into an AI-native platform by enabling intelligent discovery, understanding, and utilization of enterprise data.
  • Design and implement AI-driven capabilities and agents that enhance data platform capabilities, automate complex workflows, and improve how data is discovered, managed, governed, and consumed.
  • Build the data intelligence foundation required for AI systems, including trusted context, business understanding, and reliable access to enterprise data.
  • Design architectures that enable AI systems to reason over enterprise data and safely interact with platform capabilities, APIs, services, and enterprise applications.
  • Develop scalable AI-enabled solutions that integrate with cloud data platforms, distributed systems, and modern software architectures.
  • Establish engineering practices for reliable production AI capabilities, including security, governance, evaluation, monitoring, and operational excellence.
  • Apply strong data engineering and software engineering principles to build scalable, maintainable AI-enabled platform capabilities.
  • Partner with data, AI/ML, architecture, and product teams to identify and deliver high-impact AI capabilities for the enterprise data platform.
  • Mentor engineers and define best practices for AI-enabled data platform development.

What We are Looking For:

  • 8-12+ years of experience in enterprise software engineering, cloud data engineering, distributed systems, or data platform development.
  • Hands-on experience designing and building production AI systems, AI agents, or agentic workflows integrated with enterprise applications, APIs, and platform services.
  • Strong understanding of AI agent architectures, including tool calling, orchestration, context management, memory, evaluation, observability, and production deployment patterns.
  • Experience building AI-ready data platforms with capabilities such as semantic understanding, metadata intelligence, context engineering, and trusted data access.
  • Strong cloud data engineering experience, preferably in GCP, including BigQuery, Pub/Sub, Dataflow/Cloud Run, Composer/Airflow, and modern data platform services.
  • Strong programming skills in Python and experience building scalable software services, APIs, and microservice architectures.
  • Deep understanding of data engineering fundamentals, including data modeling, data contracts, metadata, lineage, governance, data quality, and batch/streaming architectures.
  • Experience integrating AI capabilities with enterprise data platforms and distributed systems.
  • Experience with modern data and cloud-native technologies such as Iceberg, Trino, Kubernetes, and Docker.
  • Experience designing secure, governed, and observable production AI solutions, including evaluation, monitoring, and operational excellence.

What Will Set You Apart:

  • Experience building AI agents that execute real-world enterprise workflows, beyond conversational assistants or prototypes.
  • Experience with AI frameworks and platforms such as Google ADK, Vertex AI, MCP, LangGraph, or similar technologies.
  • Experience applying RAG, embeddings, vector search, semantic layers, or knowledge graphs to enterprise AI solutions.
  • Experience with Data Mesh, domain-driven data architecture, or federated data platforms.
  • Supply chain, logistics, warehouse automation, or industrial domain experience.

Location & Authorization:This is a hybrid role requiring proximity to one of our U.S. offices (Atlanta GA, Grand Rapids MI, Milwaukee WI).Applicants must be authorized to work in the U.S. without the need for current or future sponsorship.

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