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Data Analytics Engineer Jobs in Georgia (NOW HIRING)

Apex Informatics

DECAL Analytics Engineer

Atlanta, GA · On-site

Atlanta, GA 3+ years of experience in data engineering or analytics engineering roles. Required 3 Years Advanced SQL: Proficiency in advanced SQL techniques for data transformation, querying, and ...

Wayne Farms LLC

Data & Analytics Lead - IT

Oakwood, GA · On-site

Review and contribute to analytics engineering code with a focus on correctness, performance, and ... Implement data quality checks, validation tests, and monitoring * Implement data quality checks ...

Premier Truck Rental

Senior Analytics Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Working closely with Data Engineering, Data Architecture, and the BI team, you will translate ... Mentor Analytics Engineer I / junior engineers, review their code, and set the modeling patterns ...

Workday, Inc.

Sr Analytics Engineer

Atlanta, GA · On-site

$160K - $216K/yr

Partner closely with analytics engineers and data architects to deeply understand the underlying data models in Snowflake and develop a profound understanding of our business domains and data ...

Metabo

Senior Data & Analytics Specialist

Braselton, GA · On-site

Consulting and requirements engineering with and for key stakeholders within USA & North America. * Project Management, consulting and development for global Data & Analytics projects with focus on ...

Rivian

Senior People Analytics Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Role Summary Rivian is seeking a passionate and data-driven Senior Analytics Engineer to join our People Systems Team. In this pivotal role, you'll be instrumental in delivering impactful insights ...

Salesforce

DATA ANALYST/BI ENGINEER

Atlanta, GA · On-site

This individual should be able to work across the full analytics lifecycle: sourcing and engineering data, understanding lineage and dependencies, designing curated datasets, applying business logic ...

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Showing results 21-40

All JobsData Analytics Engineer JobsData Analytics Engineer Jobs in Georgia

Data Analytics Engineer information

See Georgia salary details

$37.6K

$109.5K

$149.9K

How much do data analytics engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for data analytics engineer in Georgia is $109,530.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,700.00 and $116,100.00 per year, depending on experience, location, and employer.

How do data analytics engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

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

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

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

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to develop insights and reports.

What are the most commonly searched types of Data Analytics Engineer jobs in Georgia?

The most popular types of Data Analytics Engineer jobs in Georgia are:

What are popular job titles related to Data Analytics Engineer jobs in Georgia?

For Data Analytics Engineer jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Data Analytics Engineer jobs in Georgia look for?

The top searched job categories for Data Analytics Engineer jobs in Georgia are:

What cities in Georgia are hiring for Data Analytics Engineer jobs?

Cities in Georgia with the most Data Analytics Engineer job openings:

Data Analytics Engineer jobs near you
Infographic showing various Data Analytics Engineer job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $109,530 per year, or $52.7 per hour.

DECAL Analytics Engineer

Apex Informatics

Atlanta, GA • On-site

Other

Re-posted 17 days ago

Job description

Role: DECAL Analytics Engineer
Location: Atlanta, GA
JOB DESCRIPTION
3+ years of experience in data engineering or analytics engineering roles.
Required
3
Years
Advanced SQL: Proficiency in advanced SQL techniques for data transformation, querying, and optimization.
Required
3
Years
Azure Databricks (Spark, Delta Lake)
Required
3
Years
Microsoft Fabric (Dataflows, Pipelines, OneLake)
Required
3
Years
SQL and Python (Pandas, PySpark)
Required
3
Years
The Analytics Engineer will contribute to our modern data estate strategy by developing scalable data solutions using Microsoft Fabric and Azure Databricks. This role will be instrumental in building resilient data pipelines, transforming raw data into curated datasets, and delivering analytics-ready models that support enterprise-level reporting and decision-making.
Work Location & Attendance Requirements:
• Must be physically located in Georgia
• On-site: Tuesday to Thursday, per manager's discretion
• Mandatory in-person meetings:
o All Hands
o Enterprise Applications
o On-site meetings
o DECAL All Staff
• Work arrangements subject to management's decision
Key Responsibilities:
Data Engineering & Pipeline Development
• Build and maintain ETL/ELT pipelines using Azure Databricks and Microsoft Fabric.
• Implement medallion architecture (Bronze, Silver, Gold layers) to support data lifecycle and quality.
• Develop real-time and batch ingestion processes from IES Gateway and other source systems.
• Ensure data quality, validation, and transformation logic is consistently applied.
• Use Python, Spark, and SQL in Databricks and Fabric notebooks for data transformation.
• Delta Lake: Implementing Delta Lake for data versioning, ACID transactions, and schema enforcement.
• Integration with Azure Services: Integrating Databricks with other Azure services like Azure One Lake, Azure ADLS Gen2, and Microsoft fabric.
Data Modeling & Curation
• Collaborate with the Domain Owners to design dimensional and real-time data models.
• Create analytics-ready datasets for Power BI and other reporting tools.
• Standardize field naming conventions and schema definitions across datasets.
Data Governance & Security
• Apply data classification and tagging based on DECAL's data governance framework.
• Implement row-level security, data masking, and audit logging as per compliance requirements.
• Support integration with Microsoft Purview for lineage and metadata management.
Data Modeling:
• Dimensional modeling
• Real-time data modeling patterns
Reporting & Visualization Support
• Partner with BI developers to ensure data models are optimized for Power BI.
• Provide curated datasets that align with reporting requirements and business logic.
• Create BI dashboards and train users.
DevOps & Automation
• Support CI/CD pipelines for data workflows using Azure DevOps.
• Assist in monitoring, logging, and performance tuning of data jobs and clusters.
Required Qualifications:
• Bachelor's degree in computer science, Data Engineering, or related field.
• 3+ years of experience in data engineering or analytics engineering roles.
• Advanced SQL: Proficiency in advanced SQL techniques for data transformation, querying, and optimization.
• Hands-on experience with:
o Azure Databricks (Spark, Delta Lake)
o Microsoft Fabric (Dataflows, Pipelines, OneLake)
o SQL and Python (Pandas, PySpark)
o SQL Server 2019+
• Familiarity with data modeling, data governance, and data security best practices.
• Strong understanding of ETL/ELT processes, data quality, and schema design.
Preferred Skills:
• Experience with Power BI datasets and semantic modeling.
• Knowledge of Microsoft Purview, Unity Catalog, or similar governance tools.
• Exposure to real-time data processing and streaming architectures.
• Knowledge of federal/state compliance requirements for data handling
• Familiarity with Azure DevOps, Terraform, or CI/CD for data pipelines.
Certifications (preferred):
• Microsoft Fabric Analytics Engineer.
Soft Skills:
• Strong analytical and problem-solving abilities.
• Excellent communication skills for technical and non-technical audiences.
• Experience working with government stakeholders.

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