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Data Engineer Jobs in Powder Springs, GA (NOW HIRING)

Data Engineer

Atlanta, GA

$110K - $132K/yr

The Data Engineer designs, builds, and supports the data pipelines, integrations, and curated datasets that power analytics, reporting, and AI initiatives for PBK's Architecture vertical and broader ...

Data Engineer

Atlanta, GA

$110K - $132K/yr

Role: Data Engineer Location: Atlanta, GA Duration: 6+Month Contract 5 years of experience with at least one statistical programming language: Python, R, SAS, Julia (Python Preferred) 5 years of ...

Data Engineer

Kennesaw, GA · On-site

$105K - $127K/yr

Yamaha Motor Corporation, USA is seeking a Data Engineer to join their Digital Transformation group in Kennesaw, GA. This role involves designing, building, and scaling a Customer Data Platform (CDP ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Role: Data Engineer Location: Atlanta, GA Duration: 6+Month Contract 5 years of experience with at least one statistical programming language: Python, R, SAS, Julia (Python Preferred) 5 years of ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Job Title Data Engineer Summary Key Objectives: Supports the development, optimization, and maintenance of Cushman & Wakefield's commercial real estate (CRE) forecasting infrastructure across the ...

Data Engineer

Atlanta, GA · On-site +1

$105K - $140K/yr

We are looking for a Data Engineer to join our Data Engineering team and help build the data infrastructure that powers analytics, machine learning, and business decision-making at PrizePicks. This ...

Data Engineer

Atlanta, GA · On-site +1

$105K - $140K/yr

We are looking for a Data Engineer 1 to join our Data Engineering team and help build the data infrastructure that powers analytics, machine learning, and business decision-making at PrizePicks. This ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Job Title Data Engineer Summary Key Objectives: Supports the development, optimization, and maintenance of Cushman & Wakefield's commercial real estate (CRE) forecasting infrastructure across the ...

Data Engineer

Atlanta, GA

$110K - $132K/yr

Job Title Data Engineer Summary Key Objectives: Supports the development, optimization, and maintenance of Cushman & Wakefield's commercial real estate (CRE) forecasting infrastructure across the ...

Data Engineer

Atlanta, GA

$110K - $132K/yr

Job Title Data Engineer Summary Key Objectives: Supports the development, optimization, and maintenance of Cushman & Wakefield's commercial real estate (CRE) forecasting infrastructure across the ...

Data Engineer

Kennesaw, GA

$105K - $127K/yr

Yamaha has an opportunity for a Data Engineer to join our Digital Transformation group in Kennesaw, GA (relocation not available). This position will design, build, and scale a Customer Data Platform ...

Data Engineer

Kennesaw, GA · On-site

$105K - $127K/yr

Yamaha has an opportunity for a Data Engineer to join our Digital Transformation group in Kennesaw, GA (relocation not available). This position will design, build, and scale a Customer Data Platform ...

Data Engineer Advisor

Atlanta, GA · On-site

$90 - $95/hr

We are currently seeking a Sr Data Engineer - Advisor to join our team in Atlanta, Georgia (US-GA), United States (US). Position Overview We are seeking a Senior Data Engineer to join the core ...

Data Engineer

Kennesaw, GA · On-site

$105K - $127K/yr

Yamaha has an opportunity for a Data Engineer to join our Digital Transformation group in Kennesaw, GA (relocation not available). This position will design, build, and scale a Customer Data Platform ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Data Engineer Location: Berkeley Heights, NJ/Atlanta, GA (Hybrid) Duration: 6 months Contract to hire role Note : Need Snowflake experience * The candidate will be responsible for building out a new ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Job Summary We are seeking a hands-on Data Engineer to support a large-scale migration initiative focused on modernizing financial and regulatory reporting systems. This role will be responsible for ...

Azure Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Azure Data Engineer Location : Atlanta, GA Remote Duration : Long-Term We are looking for an experienced data engineer to join our team. You will use various methods to transform raw data into useful ...

Data Engineer IV

Atlanta, GA · On-site

$110K - $132K/yr

Data Engineer IV - Modern Enterprise / Lakehouse / AI-Assisted Location: 241 Ralph McGill Blvd, Atlanta GA, 30308 HYBRID Duration: 6 Months Client: Georgia Power Position Overview The Data Engineer ...

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Data Engineering Lead (Marketing) Position Description (General role information, job purpose, main objectives of the role) Location: Atlanta, GA Duration: FULL TIME / C2H Mode: Hybrid ( 3 days a ...

Sr Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Data Engineering Lead (Marketing) Position Description (General role information, job purpose, main objectives of the role) Location: Atlanta, GA Duration: FULL TIME / C2H Mode: Hybrid ( 3 days a ...

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Data Engineer information

See Powder Springs, GA salary details

$42.1K

$122.8K

$168.1K

How much do data engineer jobs pay per year?

As of Jun 30, 2026, the average yearly pay for data engineer in Powder Springs, GA is $122,832.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,400.00 and $130,200.00 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.

Are data engineers highly paid?

Data engineers are generally well-paid due to their specialized skills in designing and maintaining data infrastructure, with salaries often higher than many other IT roles. Compensation varies based on experience, location, and industry, but strong technical skills in programming, databases, and cloud platforms typically lead to higher earnings.

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 are Data Engineers?

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.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipeline tools. Entry-level data engineering positions may be available for candidates with relevant internships or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect some prior experience. Certifications or coursework in data management can also be beneficial for those starting out.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and leadership roles can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of expertise and a strong track record in data architecture and engineering.
What are the most commonly searched types of Data Engineer jobs in Powder Springs, GA? The most popular types of Data Engineer jobs in Powder Springs, GA are:
What are popular job titles related to Data Engineer jobs in Powder Springs, GA? For Data Engineer jobs in Powder Springs, GA, the most frequently searched job titles are:
What job categories do people searching Data Engineer jobs in Powder Springs, GA look for? The top searched job categories for Data Engineer jobs in Powder Springs, GA are:
What cities near Powder Springs, GA are hiring for Data Engineer jobs? Cities near Powder Springs, GA with the most Data Engineer job openings:
Infographic showing various Data Engineer job openings in Powder Springs, GA as of June 2026, with employment types broken down into 2% As Needed, 88% Full Time, 7% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,832 per year, or $59.1 per hour.

$110K - $132K/yr

Full-time

Posted 7 days ago


Job description

The Data Engineer designs, builds, and supports the data pipelines, integrations, and curated datasets that power analytics, reporting, and AI initiatives for PBK's Architecture vertical and broader AEC operations. This role owns integrations across enterprise platforms, including Salesforce, Deltek Vantagepoint, Autodesk data sources, Azure, and Microsoft Fabric. The Data Engineer ensures data is reliable, governed, secure, and available to support business visibility, project delivery, automation, and decision-making.


Your Impact:

  • Design, build, operate, and support ETL/ELT pipelines and integrations across enterprise systems, including Salesforce, Deltek Vantagepoint, Autodesk data sources, Azure, and Microsoft Fabric.
  • Implement data models, curated datasets, Lakehouse/Warehouse structures, and transformation layers to support BI, reporting, AI, and machine learning use cases.
  • Build and support API-first data services, data contracts, and integration workflows using REST, JSON, SOAP where applicable, webhooks, and related patterns.
  • Develop orchestration and scheduling processes using Microsoft Fabric Data Pipelines, Azure Data Factory, Azure Logic Apps, Functions, Spark notebooks, dbt, or similar tools.
  • Apply event-driven integration patterns using Event Grid, Service Bus, Kafka concepts, or similar technologies where appropriate.
  • Own the operational reliability of pipelines and integrations, including monitoring, alerting, incident response, troubleshooting, root-cause analysis, and remediation.
  • Implement data quality checks, validation, lineage, documentation, and governance practices to ensure data is accurate, trusted, and usable.
  • Partner with analytics, application, IT/Security, and business teams to support secure access, data governance, compliance, and reliable data delivery.
  • Support AI initiatives by preparing reliable datasets, including AI/ML pipelines or RAG-oriented datasets where applicable.
  • Use AI tools responsibly to improve productivity, accelerate development, support testing, and improve documentation while maintaining security and quality standards.

Here's What You'll Need:

  • 5+ years of experience designing, building, and operating production data pipelines and integrations.
  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field; directly relevant experience, certifications, or training demonstrating comparable expertise in data pipelines, integrations, cloud data platforms, APIs, data governance, and secure data workflows may be considered in lieu of a degree.
  • Strong SQL skills and experience with PostgreSQL or similar relational databases.
  • Proficiency in Python for data engineering, automation, and workflow development.
  • Hands-on experience with Microsoft Azure data services and Microsoft Fabric, or equivalent cloud data platforms.
  • Experience with ETL/ELT pipelines, data modeling, curated datasets, orchestration, and production data workflows.
  • Strong experience with APIs and integration patterns, including REST, webhooks, authentication, error handling, retry strategies, and cross-system data movement.
  • Familiarity with SDLC and CI/CD for data workflows using GitHub Enterprise, Azure DevOps, or similar tools.
  • Strong understanding of security, data governance, access controls, and secure handling of sensitive business information.
  • Ability to communicate clearly with technical and non-technical stakeholders in an AEC or similar business environment.
  • Operational discipline with the ability to maintain, monitor, troubleshoot, and improve mission-critical data flows over time.

Here's How You'll Stand Out:

  • Experience integrating enterprise platforms such as Salesforce, Deltek Vantagepoint, Autodesk Forma, Autodesk data management services, Microsoft 365, or similar systems.
  • Experience with Azure Logic Apps, Azure Functions, MuleSoft, Databricks, Snowflake, or other iPaaS/middleware and cloud data platforms.
  • Experience with dbt, Airflow, Databricks Workflows/Jobs, Fabric notebooks, Spark, or similar transformation and orchestration frameworks.
  • Experience with streaming or event-driven integrations using Event Grid, Service Bus, Kafka concepts, or similar technologies.
  • Experience with Power BI semantic models, performance optimization, and BI-ready dataset design.
  • Experience supporting AI/ML pipelines, RAG-oriented datasets, or data products used in AI-enabled workflows.
  • Strong integration owner mindset with the ability to build solutions that are maintainable, observable, secure, and supportable.
  • Business-oriented approach with a focus on data outcomes that improve delivery, visibility, automation, and decision-making.