1

Data Engineer Jobs in Augusta, GA (NOW HIRING)

Engineering, Research & Development Reports to: Metallurgical and Materials R&D Lab Manager ... You'll build the data foundation that powers this work, implement and train models that bridge ...

Collaborating with engineering, project management, and consultancy teams to understand requirements, shape analytical approaches, and communicate findings. * Monitoring data quality, identifying ...

Job Brief Data Science, Machine Learning, Programming Are you VIGILANT about your career? RealmOne definitely is! RealmOne was built on the principle that people matter first and foremost. We believe ...

Job Brief Data Science, Machine Learning, Programming Are you VIGILANT about your career? RealmOne definitely is! RealmOne was built on the principle that people matter first and foremost. We believe ...

Element has an opportunity for a Data Processor to join our rapidly expanding team. As a member of ... Propose engineering documents for clients' approval, on-site installation and hands-on monitoring ...

Showing results 21-40

Data Engineer information

See Augusta, GA salary details

$41.4K

$120.6K

$165.1K

How much do data engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for data engineer in Augusta, GA is $120,625.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,500.00 and $127,900.00 per year, depending on experience, location, and employer.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

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

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipelines. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience and proficiency with tools like SQL, Python, and cloud platforms.
What are the most commonly searched types of Data Engineer jobs in Augusta, GA? The most popular types of Data Engineer jobs in Augusta, GA are:
What job categories do people searching Data Engineer jobs in Augusta, GA look for? The top searched job categories for Data Engineer jobs in Augusta, GA are:
What cities near Augusta, GA are hiring for Data Engineer jobs? Cities near Augusta, GA with the most Data Engineer job openings:
Infographic showing various Data Engineer job openings in Augusta, GA as of August 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 94% In-person, 3% Hybrid, and 3% Remote job distribution, with an average salary of $120,625 per year, or $58 per hour.

Machine Learning Engineer

Ksb

Grovetown, GA • On-site

Full-time

Re-posted 2 days ago


Job description

KSB is a leading supplier of pumps, valves and related service. Our reliable, high-efficiency products are used in applications wherever fluids need to be transported or shut off, covering everything from building services,industry and water transport to waste water treatment, power plant processes and mining. Founded in 1871 in Frankenthal, Germany, the company has a presence on all continents with its own sales and marketing organisations and manufacturing facilities. Around the globe, more than 190 service centres and around 3,500 service specialists are on hand to provide local inspection, servicing, maintenance and repair services under the KSB SupremeServ brand. Innovative technology that is the fruit of KSB's research and development activities forms the basis for the company's success.
People. Passion. Performance. It is these three success factors that make KSB the company it is today.
At KSB, we recognise that it is people who actually make the difference - the people we employ and the people we serve. This is why we are committed to equal rights and treatment worldwide and never lose sight of the aspects ecology and sustainability when manufacturing our products.

Machine Learning Engineer KSB GIW, Inc.

Department: Engineering, Research & Development
Reports to: Metallurgical and Materials R&D Lab Manager
Location: Grovetown, GA, USA (onsite)
Shift: First

FLSA Status: Salary Exempt

OVERVIEW:

Our R&D group is expanding its use of machine learning to solve real engineering problems, and we're looking for a sharp, hands-on early-career engineer to join the team.

You'll work at the intersection of machine learning and the physical world to build AI systems that learn from real industrial data and connect with the engineering models behind them. The role lives where machine learning meets scientific computing: surrogate modeling, data-driven approximations of physical systems, and ML models that respect the underlying engineering principles.

You'll build the data foundation that powers this work, implement and train models that bridge physics-based simulation with modern machine learning, and work closely with an experienced technical lead who will guide your growth across data engineering, scientific ML, and emerging AI tooling.

RESPONSIBILITIES:

  • Build and maintain the data foundation: ingestion, cleaning, transformation, validation, and metadata standards
  • Implement and train machine learning models using Python and modern frameworks (PyTorch)
  • Contribute to applied AI tooling that supports the broader R&D workflow
  • Develop visualization and dashboard interfaces that present results to end users
  • Run experiments, track results, and report findings against defined targets
  • Help bring prototype code to production quality: testing, documentation, version control
  • Collaborate with team members across engineering disciplines

QUALIFICATIONS:

  • Education:Bachelor's degree required; master's preferred in Computer Science, Engineering, Applied Math, Physics, or a related field
  • Experience:1-3 years of professional or substantial project experience in machine learning, data engineering, or scientific computing

SKILLS / COMPETENCIES

Required:
  • Solid Python skills with hands-on experience using core libraries:
    • Machine learning: PyTorch, scikit-learn
    • Data: NumPy, pandas
    • Scientific computing: SciPy, Matplotlib
  • Foundational understanding of scientific computing: numerical methods, simulation concepts, or modeling of physical systems - this is essential to the role
  • Foundational understanding of neural networks, model training, and optimization
  • Experience with version control (Git) and working in a Linux environment
  • Strong written and verbal communication skills
  • Collaborative, coachable attitude
Preferred:
  • Experience building and maintaining data pipelines, metadata schemas, and data quality frameworks
  • Exposure to scientific / physics-informed machine learning (surrogate modeling, embedding physical constraints into ML models)
  • Background in CFD, simulation, computational mechanics, or applied physics
  • Familiarity with agentic AI / LLM frameworks (LangChain, LangGraph, or similar) enough to collaborate effectively, not lead
  • Experience with Jupyter, Docker, MLflow, or FastAPI
  • Front-end / dashboard development experience (React)
  • Cloud compute (AWS or Azure) and GPU-based training
  • Coursework or research projects in numerical methods, engineering, or applied science

PHYSICAL REQUIREMENTS:

  • Primarily desk-type duty

KSB Group is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.

This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. KSB makes hiring decisions based solely on qualifications, merit, and business needs at the time.

We value employees who take the initiative and are committed to our company; Employees who take responsibility and for whom business success is the focus of their actions. In return, we offer fair framework conditions for collective wages and pensions, flexible working time models, individual training opportunities and the best career prospects.