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Full Time Data Engineering Jobs in Atlanta, GA (NOW HIRING)

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

Provide technical guidance and best practices to the data engineering and business teams ... This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or ...

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

Provide technical guidance and best practices to the data engineering and business teams ... This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or ...

Data Engineer - GCP

Atlanta, GA · On-site

$110K - $132K/yr

Provide technical guidance and best practices to the data engineering and business teams ... This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or ...

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Atlanta, GA Duration: FULL TIME / C2H Mode: Hybrid ( 3 days a Week) This Data Engineering Lead (Marketing) position is part of Client IT's Marketing Technology team focused on enabling the ...

Atlanta, GA Duration: FULL TIME / C2H Mode: Hybrid ( 2 days a Week) This Data Engineering Lead (Marketing) position is part of Client IT's Marketing Technology team focused on enabling the ...

Azure Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Data Engineer Duration: FULL TIME (Accepting H1B Transfer ) Location: Atlanta, GA - On-Site ( Hybrid) Data Engineer (ONSITE)- Receive requests from Business and perform architectural assessment and ...

Bachelor's degree in computer science, Engineering, Applied Mathematics or related STEM field * Minimum of 4 years of full time Data Science prototyping experience (Python) using machine learning ...

Bachelor's degree in computer science, Engineering, Applied Mathematics or related STEM field * Minimum of 4 years of full time Data Science prototyping experience (Python) using machine learning ...

Bachelor's degree in computer science, Engineering, Applied Mathematics or related STEM field * Minimum of 4 years of full time Data Science prototyping experience (Python) using machine learning ...

Lead Data Engineer

Atlanta, GA · On-site

$98K - $129K/yr

Location: Atlanta, GA (Hybrid) **Mode: FullTime **Note: Only USC and GC can apply ... Requirements:** - Expert years of hands-on experience in Data Engineering across On-Premises and ...

Data Engineer

Atlanta, GA · On-site +1

$105K - $140K/yr

Develop and execute well-defined data engineering tasks - creating and modifying data models ... In addition to your great compensation package, full-time employees will be eligible for the ...

Data Engineer

Alpharetta, GA · Hybrid

$111K - $134K/yr

Contribute to engineering standards and participate in design reviews. * Partner with offshore ... The position is full-time with work-from-home options, requiring in-office presence three (3) days ...

Data Architect

Atlanta, GA · On-site

$62.25 - $80/hr

Atlanta, GA Role: Full Time Mode: On-Site Accepting H1B Transfer cases This role is a hands-on ... Azure DevOps,

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Showing results 1-20

Full Time Data Engineering information

See Atlanta, GA salary details

$42.8K

$124.7K

$170.7K

How much do full time data engineering jobs pay per year?

As of Jul 27, 2026, the average yearly pay for full time data engineering in Atlanta, GA is $124,743.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,100.00 and $132,200.00 per year, depending on experience, location, and employer.

Is there a high demand for data engineers?

Data engineering is a highly sought-after role due to the increasing reliance on data-driven decision making across industries. The demand for skilled data engineers with expertise in tools like SQL, Python, and cloud platforms continues to grow, leading to strong job prospects and competitive salaries.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their expertise in tools like SQL, Spark, and cloud platforms remains critical for managing data workflows and ensuring data quality.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, and other incentives.

What engineers make $300,000 a year?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn $300,000 or more annually. High compensation is often associated with roles in large organizations, specialized expertise, and leadership responsibilities in data infrastructure projects.

What are the key skills and qualifications needed to thrive as a Full Time Data Engineer, and why are they important?

To thrive as a Full Time Data Engineer, you need strong programming skills (such as Python or Java), proficiency in SQL, and a solid understanding of data modeling and ETL processes, usually supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop or Spark), cloud platforms (such as AWS or Azure), and relevant certifications (e.g., Google Cloud Data Engineer) is highly valuable. Excellent problem-solving, communication, and teamwork abilities distinguish top performers in this role. These skills ensure efficient data infrastructure development, reliable data pipelines, and effective collaboration with cross-functional teams to support business objectives.

What are full time data engineering jobs?

Full time data engineering jobs involve building, managing, and optimizing data pipelines and infrastructure to collect, process, and store large volumes of data for organizations. Data engineers work with technologies like SQL, Python, cloud platforms, and big data tools to ensure data is reliable and accessible for analytics and business decision-making. These roles typically require strong programming skills, knowledge of database systems, and experience with data modeling and ETL (Extract, Transform, Load) processes. Full time positions generally offer benefits and require a standard workweek commitment, often in tech, finance, healthcare, or other data-driven industries.

What is the difference between Full Time Data Engineering vs Part Time Data Engineering?

AspectFull Time Data EngineeringPart Time Data Engineering
Work HoursTypically 40 hours/weekLess than 20 hours/week
CredentialsRelevant degrees, certifications like AWS, GCP, or AzureSame as full-time, but often less emphasis on certifications
Work EnvironmentFull-time employment, often in corporate or tech firmsFreelance or contract basis, flexible locations
Job ResponsibilitiesDesigning, building, maintaining data pipelinesSupporting existing pipelines, smaller projects

Full Time Data Engineering involves a standard 40-hour workweek with comprehensive responsibilities in designing and maintaining data systems. Part Time Data Engineering offers flexible hours, often focusing on specific tasks or projects. Both roles require relevant technical skills and certifications, but full-time positions typically demand more extensive experience and commitment.

What are some common challenges faced by full-time data engineers, and how can they be addressed?

Full-time data engineers often encounter challenges such as integrating data from diverse sources, ensuring data quality, and optimizing data pipelines for scalability and performance. These issues can be addressed by adopting robust ETL (Extract, Transform, Load) frameworks, implementing automated data validation tests, and collaborating closely with data analysts and software engineers to align on data requirements. Staying updated with the latest cloud technologies and best practices in data architecture also helps in overcoming these challenges and maintaining efficient, reliable data systems.
What are the most commonly searched types of Data Engineering jobs in Atlanta, GA? The most popular types of Data Engineering jobs in Atlanta, GA are:

Data Engineer - GCP

The Data Sherpas

Atlanta, GA • On-site, Remote

$110K - $132K/yr

Full-time

Medical, Dental, Vision

Posted 17 days ago


Job description

Who We Are: 

We are a dynamic team focused on building innovative and scalable data solutions on Google Cloud Platform (GCP). Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable data pipelines and data infrastructure, ensuring data availability, accuracy, and performance for business insights and machine learning models.


What We Are Looking For: 

We are seeking an experienced and highly skilled Google Cloud Data Engineer who will be responsible for developing and managing data pipelines on GCP. The ideal candidate will bring strong expertise in cloud-based data processing, big data technologies, and data modeling to help us provide high-performance data solutions.


Responsibilities:

Data Pipeline Development and Management:

  • Design, build, and maintain scalable and reliable data pipelines using Cloud Dataflow, Cloud Pub/Sub, and Cloud Composer.
  • Develop ETL/ELT processes to process and transform large volumes of structured and unstructured data.
  • Optimize data pipeline performance, scalability, and reliability.
  • Ensure data processing and ingestion workflows are monitored and meet performance SLAs.

Data Storage and Management:

  • Design and implement data storage solutions using BigQuery, Cloud Storage, and Firestore.
  • Optimize data structures and partitioning for performance and cost efficiency.
  • Ensure data security, integrity, and availability in all storage solutions.
  • Manage data lifecycle policies and archiving processes.

Data Transformation and Processing:

  • Develop data transformation processes using BigQuery, Apache Beam, and Cloud Functions.
  • Implement data quality checks, validation rules, and monitoring solutions.
  • Support real-time and batch data processing needs.

Data Integration and Automation:

  • Integrate data from multiple sources, including APIs, databases, and third-party applications.
  • Automate data ingestion, transformation, and export using tools like Cloud Composer and Cloud Functions.
  • Ensure data consistency across different environments and systems.

Collaboration and Stakeholder Engagement:

  • Work closely with data scientists and analysts to understand data needs and business goals.
  • Provide technical guidance and best practices to the data engineering and business teams.
  • Collaborate with security and compliance teams to ensure data governance standards are met.

Performance Monitoring and Troubleshooting:

  • Monitor data pipeline performance and troubleshoot issues in real-time.
  • Analyze data pipeline failures and implement fixes to prevent recurrence.
  • Set up logging and monitoring using Stackdriver and Cloud Monitoring.


Qualifications:

  • Bachelor’s degree in Computer Science, Data Engineering, or a related field; Master’s degree is a plus.
  • 3+ years of experience in data engineering, with at least 2+ years working with Google Cloud Platform.
  • Google Professional Data Engineer certification is required.
  • Strong proficiency with GCP services such as BigQuery, Cloud Dataflow, Cloud Composer, Cloud Pub/Sub, Firestore, and Cloud Functions.
  • Hands-on experience with big data tools and frameworks such as Apache Beam, Hadoop, Spark, or Flink.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Strong knowledge of SQL, data modeling, and query optimization.
  • Experience with CI/CD tools and version control (e.g., Git, Cloud Build).
  • Strong understanding of data governance, security, and compliance requirements.
  • Ability to manage large-scale data processing and real-time data pipelines.
  • Excellent problem-solving, analytical, and communication skills.


Preferred Skills:

  • Experience with machine learning pipelines and AI/ML model deployment.
  • Familiarity with Terraform and Infrastructure as Code (IaC) principles.
  • Experience with NoSQL databases and key-value stores on GCP.
  • Knowledge of containerization and orchestration using Google Kubernetes Engine (GKE).


What We Offer:

  • Competitive salary and performance-based incentives.
  • Comprehensive health, dental, and vision coverage.
  • Professional development and training opportunities (including GCP certification).
  • Flexible work environment and remote work options.


Join us and be part of a team building innovative and scalable data solutions on Google Cloud Platform!


This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or Corp-to-Corp (C2C) arrangements. We are looking for the best talent and are flexible on the employment structure for the right candidate.


We cannot work with third-party agencies at this time. Resumes submitted via unapproved agencies will be automatically rejected.