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Data Engineer Ml Jobs in Decatur, GA (NOW HIRING)

QGenda

Senior Data Engineer

Atlanta, GA · Hybrid

$101K - $138K/yr

About Your Role As a Senior Data Engineer, you will design, build, and optimize the data platform ... Experience preparing datasets and data structures for AI/ML use cases, including NLP-driven ...

Worldpay

ML Software Engineering Lead

Atlanta, GA · On-site

$98K - $129K/yr

In this strategic role, you will collaborate closely with product, data science, platform engineers, and other product delivery teams to translate ML models and data-driven algorithms into robust ...

Aveva

Senior Data Engineer

Alpharetta, GA

$103K - $140K/yr

Senior AI Data Engineer Location: Atlanta, GA (Hybrid) Organization: RIB North America (RIB NAM ... Exposure to building pipelines for AI/ML or Agentic AI use cases * Solid understanding of ...

Accenture

Google Data Specialist

Atlanta, GA · On-site

$70K - $196K/yr

Collaborate closely with senior data engineers, ML engineers, and architects. * Contribute to ... internal accelerators, documentation, and reusable components. * Stay current with GCP releases ...

AVEVA Group

Senior Data Engineer

Alpharetta, GA · On-site

$103K - $140K/yr

Senior AI Data Engineer Location: Atlanta, GA (Hybrid) Organization: RIB North America (RIB NAM ... Exposure to building pipelines for AI/ML or Agentic AI use cases * Solid understanding of ...

R2 Technologies Corporation

Big Data Engineer

Alpharetta, GA · On-site

$54.50 - $72/hr

Big Data Engineer Joining Location: Remote due to Covid but eventually (Alpharetta, GA) # of ... We are transforming corporations through deep domain expertise, knowledge-based ML platforms, as ...

QGenda

Senior Data Engineer

Atlanta, GA · On-site

$101K - $138K/yr

About Your Role As a Senior Data Engineer, you will design, build, and optimize the data platform ... Experience preparing datasets and data structures for AI/ML use cases, including NLP-driven ...

QGenda

Senior Data Engineer

Atlanta, GA · On-site

$101K - $138K/yr

About Your Role As a Senior Data Engineer, you will design, build, and optimize the data platform ... Experience preparing datasets and data structures for AI/ML use cases, including NLP-driven ...

Aimpoint Digital

Lead Data Engineer 2026- US

Atlanta, GA · On-site +1

$110K - $132K/yr

Collaborate with analytics, data science, and ML project teams to productionize AI-enabled ... As a Lead Data Engineer, you will be expected to work independently on client engagements or to ...

Aimpoint Digital

Lead Data Engineer 2026- US

Atlanta, GA · On-site

$110K - $132K/yr

Collaborate with analytics, data science, and ML project teams to productionize AI-enabled ... As a Lead Data Engineer, you will be expected to work independently on client engagements or to ...

Aimpoint Digital

Lead Data Engineer 2026- US

Atlanta, GA · On-site

$110K - $132K/yr

Collaborate with analytics, data science, and ML project teams to productionize AI-enabled ... As a Lead Data Engineer, you will be expected to work independently on client engagements or to ...

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Showing results 41-60

All JobsData Engineer Ml JobsData Engineer Ml Jobs in Decatur, GA

Data Engineer Ml information

See Decatur, GA salary details

$44.9K

$161.1K

$237.7K

How much do data engineer ml jobs pay per year?

As of Aug 20, 2026, the average yearly pay for data engineer ml in Decatur, GA is $161,113.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,300.00 and $166,000.00 per year, depending on experience, location, and employer.

What does a data engineer ML do?

A Data Engineer ML (Machine Learning) is responsible for designing, building, and maintaining the data pipelines and infrastructure necessary for machine learning applications. They clean, process, and organize large datasets to ensure data quality and accessibility for data scientists and ML engineers. In addition, they may work on deploying machine learning models to production environments and optimizing data workflows for efficiency and scalability.

What are the key skills and qualifications needed to thrive as a data engineer ML?

To thrive as a Data Engineer ML, you need strong programming skills (especially in Python or Scala), knowledge of data modeling, and a solid foundation in database technologies, typically supported by a degree in computer science or a related field. Familiarity with big data frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and ETL tools, as well as relevant certifications, is highly beneficial. Excellent problem-solving abilities, teamwork, and clear communication help you collaborate with data scientists and stakeholders effectively. These skills are essential for building robust data pipelines and infrastructure that enable scalable, high-quality machine learning solutions.

How do data engineer ML roles typically collaborate with data scientists and machine learning engineers on projects?

Data Engineer ML professionals work closely with data scientists and machine learning engineers by building and maintaining robust data pipelines, ensuring clean and reliable datasets are readily available for modeling and analysis. They often participate in meetings to understand model requirements, help optimize data storage for performance, and support the deployment of machine learning models into production environments. Effective collaboration involves continuous communication to troubleshoot data issues, implement data validation, and scale solutions as project needs evolve. This teamwork ensures that data-driven projects move efficiently from experimentation to deployment.

What is the difference between Data Engineer Ml vs Data Scientist?

AspectData Engineer MlData Scientist
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science certifications
Work EnvironmentBuilding data pipelines, managing databasesAnalyzing data, creating models
Employer & Industry UsageTech companies, finance, healthcareResearch institutions, tech firms, finance

Data Engineer Ml focuses on developing and maintaining data infrastructure and pipelines, while Data Scientists analyze data and build predictive models. Both roles often collaborate but serve different functions within data teams.

What are popular job titles related to Data Engineer Ml jobs in Decatur, GA?

For Data Engineer Ml jobs in Decatur, GA, the most frequently searched job titles are:

What job categories do people searching Data Engineer Ml jobs in Decatur, GA look for?

The top searched job categories for Data Engineer Ml jobs in Decatur, GA are:

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Cities near Decatur, GA with the most Data Engineer Ml job openings:

Data Engineer Ml jobs near you

Senior Data Engineer

QGenda

Atlanta, GA • Hybrid

$101K - $138K/yr

Full-time

Re-posted 27 days ago

Job description

About Your Role 

As a Senior Data Engineer, you will design, build, and optimize the data platform, including pipelines, models, and infrastructure that power analytics, reporting, and data-driven decision making across the QGenda product lines. You will serve as a technical leader with the team, contributing to architectural direction, driving best practices, and supporting complex data initiatives. This role requires deep technical expertise, strong cross-functional collaboration, and the ability to deliver scalable, high-performing data systems that meet evolving business needs.

How You'll Make an Impact 

Deliver High-Quality, Scalable Data Engineering Solutions

  • Architect, develop, test, and maintain ELT/ETL pipelines and data workflows supporting high-volume analytics
  • Implement advanced data processing solutions and observability techniques to ensure data is accurate, fresh, and reliable
  • Design and refine data models and semantic layers that support analytical self-service and advanced reporting.
  • Build data visualizations and dashboards supporting analytics use cases

Strengthen Data Engineering Practices and Technical Standards

  • Translate complex business and analytics requirements into efficient, scalable data solutions
  • Apply best practices for version control, documentation, CI/CD, Infrastructure as Code, and data governance
  • Participate in code reviews, identify opportunities for architectural improvement,, and contribute to continuous improvement efforts

Collaborate Across Teams

  • Partner with data engineers, DBAs, managers, and business stakeholders to deliver high-impact data products
  • Provide technical guidance, informal mentorship, and support to other engineers in order to elevate team capabilities
  • Communicate technical decisions, risks, and recommendations to both technical and non-technical audiences

Drive Technical Excellence

  • Optimize data pipelines and warehouse performance for speed, cost, and scalability
  • Evaluate, prototype, and influence adoption of new tools, frameworks, and architectural patterns that enhance the data platform
  • Contribute to data observability, incident response, and root-cause analysis for complex data issues
  • Design and deliver AI-ready data products, ensuring data structures, metadata, and pipelines are suitable for natural language processing, predictive analytics, and other AI-driven capabilities
Who You Are
  • Exceptional analytical, problem solving, and debugging skills
  • Strong communication with the ability to simplify and articulate technical concepts
  • Ability to work collaboratively, influence architecture, and take ownership of deliverables
  • Commitment to quality, reliability, and continuous improvement
Experience You Bring 
  • 5-7+ years in data engineering/analytics engineering, or related field
  • Bachelor's degree specializing in computing, data engineering, or related discipline
  • Expertise in distributed data processing, data modeling, and performance tuning
  • Strong proficiency in SQL and Python
  • Experience with modern data stack components, such as:
    • Cloud: AWS, GCP, Azure
    • Warehouses: Snowflake, Redshift, BigQuery, etc.
    • Orchestration: Airflow, MWAA, Composer, etc.
    • Transformation: dbt, etc.
    • Observability: data lineage/monitoring tools
    • BI: Looker, Tableau, Power BI, etc.
    • DevOps: Git, CI/CD, Terraform/CloudFormation
Not Required, But Nice to Have 
  • Experience preparing datasets and data structures for AI/ML use cases, including NLP-driven analytics
  • Experience with Glue, Dataflow

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