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Insurance Data Engineer Jobs in Georgia (NOW HIRING)

Data Engineer

Macon, GA

$109.80K - $131.90K/yr

Background in the insurance industry (including carrier experience) is a plus. Technical Competencies * Data Engineering: Experience building and supporting data warehouses/lakes, especially on ...

Data Engineer

Alpharetta, GA · On-site +1

$111.80K - $134.20K/yr

... insurance and reinsurance. We stand apart for our outstanding client service, intelligent risk ... As a Data Engineer, you will work closely with the Solution Engineer and Data Architecture teams to ...

Data Engineer

Kennesaw, GA

$105.80K - $127.10K/yr

Yamaha has an opportunity for a Data Engineer to join our Digital Transformation group in Kennesaw ... Life and AD&D Insurance * Wellness Program * Short-Term Disability Coverage (for hourly roles ...

Data Engineer

Kennesaw, GA · On-site

$105.80K - $127.10K/yr

Yamaha has an opportunity for a Data Engineer to join our Digital Transformation group in Kennesaw ... Life and AD&D Insurance * Wellness Program * Short-Term Disability Coverage (for hourly roles ...

Data Engineer

Kennesaw, GA · On-site

$105.80K - $127.10K/yr

Yamaha has an opportunity for a Data Engineer to join our Digital Transformation group in Kennesaw ... Life and AD&D Insurance * Wellness Program * Short-Term Disability Coverage (for hourly roles ...

Data Engineer

Atlanta, GA · On-site

$110.10K - $132.20K/yr

THE POSITION Our roster has an opening with your name on it We are looking for a Data Engineer to ... This role may offer the following benefits: medical, vision, and dental insurance; life insurance ...

Data Engineer

Atlanta, GA · On-site

$110.10K - $132.20K/yr

THE POSITION Our roster has an opening with your name on it We are looking for a Data Engineer to ... This role may offer the following benefits: medical, vision, and dental insurance; life insurance ...

Data Engineer

Fayetteville, GA · On-site +1

$100.60K - $120.80K/yr

We're looking for an experienced Data Engineer to help design, build, and optimize modern data ... Life Insurance * Disability Insurance * Employee Assistance Program * Flexible Spending Account You ...

Data Engineer

Atlanta, GA

$110.10K - $132.20K/yr

Recommend best practices for data modeling, governance, lineage, monitoring, DevOps, and security ... and services, banking, insurance and public administration sectors in the definition and ...

Data Engineer

Atlanta, GA · On-site

$120K - $140K/yr

Must Have Technical/Functional Skill We are looking for a Data Engineer to design, build, and ... Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional ...

Data Engineer

Atlanta, GA

$110.10K - $132.20K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is ... Therefore, we offer a comprehensive benefits package: -Health, Dental, and Vision -Life Insurance ...

Data Engineer

Atlanta, GA

$110.10K - $132.20K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is ... Therefore, we offer a comprehensive benefits package: -Health, Dental, and Vision -Life Insurance ...

Lead Data Engineer

Atlanta, GA

$110.10K - $132.20K/yr

As a Lead Data Engineer on our Industrial AI & Data Platforms team, you will architect and own the ... This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term ...

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Showing results 1-20

Insurance Data Engineer information

What are the key skills and qualifications needed to thrive as an Insurance Data Engineer, and why are they important?

To thrive as an Insurance Data Engineer, you need strong expertise in data modeling, ETL processes, and a solid understanding of insurance data structures, typically supported by a degree in computer science, data engineering, or a related field. Proficiency with SQL, Python, big data platforms (like Hadoop or Spark), and experience with cloud data solutions such as AWS or Azure are commonly required, along with certifications like AWS Certified Data Analytics or Google Cloud Data Engineer. Excellent problem-solving, communication, and collaboration skills help you bridge technical and business needs while ensuring data quality. These abilities are essential for building robust data pipelines and enabling accurate data-driven decision making within insurance organizations.

How does an Insurance Data Engineer typically collaborate with actuarial and underwriting teams?

Insurance Data Engineers work closely with actuarial and underwriting teams to ensure that the data infrastructure supports accurate risk assessment and pricing models. They often translate business requirements from these teams into technical specifications, build data pipelines to source and clean relevant data, and assist in implementing predictive analytics tools. Regular communication and collaboration are essential, as data engineers help bridge the gap between raw data and actionable insights for decision-making. This teamwork not only streamlines workflow but also enables continuous improvement of insurance products and customer experience.

What are Insurance Data Engineers?

Insurance Data Engineers are professionals who design, build, and maintain data systems that support the needs of insurance companies. They are responsible for collecting, organizing, and processing large amounts of data from various sources to enable accurate risk assessment, pricing, claims analysis, and regulatory compliance. Their work helps insurers make data-driven decisions, improve efficiency, and enhance customer experiences by leveraging modern data technologies.

What is the difference between Insurance Data Engineer vs Data Analyst in the insurance industry?

AspectInsurance Data EngineerData Analyst
Required CredentialsBachelor's in Computer Science, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentDevelops data pipelines, manages databases, works with big data toolsInterprets data, creates reports, visualizes insights
Employer & Industry UsageInsurance companies, tech firms in insuranceInsurance firms, consulting agencies, analytics companies

Insurance Data Engineers focus on building and maintaining data infrastructure, while Data Analysts interpret data to provide insights. Both roles are essential in the insurance industry but serve different functions in data management and analysis.

What are popular job titles related to Insurance Data Engineer jobs in Georgia? For Insurance Data Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Insurance Data Engineer jobs in Georgia look for? The top searched job categories for Insurance Data Engineer jobs in Georgia are:
What cities in Georgia are hiring for Insurance Data Engineer jobs? Cities in Georgia with the most Insurance Data Engineer job openings:
Infographic showing various Insurance Data Engineer job openings in Georgia as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Data Engineer

$109.80K - $131.90K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago


Job description

Data Engineer

Must be located in the Eastern or Central US Time Zone
Travel:
Occasional, based on project needs
Reports To: Chief Information Officer

We are seeking a skilled, hands-on Data Engineer to join our team. In this role, you will build, test, and maintain data pipelines and data warehouse components that support our broader data platform. You will help enable data-driven decision-making by ensuring business teams have access to clean, reliable, and well-modeled data.

As a Data Engineer, you will transform raw data into actionable insights by developing scalable pipelines, creating robust data models, and supporting reporting and analytics tools in partnership with the broader team.

Key Responsibilities

  • Data Platform Development: Build and maintain data pipelines and data warehouse/lakehouse components (data warehouses, lakes, and marts) while following established data governance, security, and privacy controls.
  • Pipeline Engineering: Develop reliable data ingestion pipelines using scheduled and event-driven patterns. Optimize performance and ensure resilience.
  • Data Quality & Monitoring: Implement data quality frameworks, validation checks, and safeguards to minimize pipeline failures and data integrity issues.
  • Architecture & Optimization: Contribute to improving legacy ingestion methods, address technical debt, and support impact assessment for proposed changes in partnership with the team.
  • Reporting & Visualization: Build custom reports and dashboards using tools like Power BI, Snowflake, etc.
  • Collaboration & Agile Delivery: Work closely with product owners and cross-functional teams to understand business needs, clarify requirements, and deliver solutions using agile methodologies.
  • Automation & Efficiency: Identify inefficiencies, automate processes, and recommend improvements to optimize data flows.
  • Documentation & Standards: Document pipelines, datasets, and data models; follow team standards; and participate in code reviews to improve maintainability and consistency.
  • Production Support: Provide technical support for production incidents, ensuring system stability and continuous improvement.

Required Qualifications

Experience: 2–4 years in data engineering with experience in Snowflake, SQL, ELT/ETL, dimensional data modeling, data warehousing, and pipeline development.

Technical Skills:

  • Strong SQL skills with experience in query optimization and basic performance tuning.
  • Solid understanding of dimensional modeling and core data architecture principles.
  • Familiarity with Azure cloud services.
  • Experience with BI tools (Power BI & Snowflake).
  • Knowledge of Agile/Scrum practices.
  • Experience building dimensional (Kimball-style) data models.

Soft Skills:

  • Excellent communication (written and verbal).
  • Strong problem-solving and incident management capabilities.
  • High attention to detail and commitment to data accuracy.

Preferred Qualifications

  • Bachelor’s degree in Computer Science, Information Systems, or related field (or equivalent experience).
  • Proficiency in programming languages such as Python or Java.
  • Experience with orchestration tools and CI/CD pipelines (e.g., ADO YAML Pipelines or GitHub Actions).
  • Familiarity with cloud platforms (Azure) and modern data tools (Snowflake).
  • Exposure to machine learning/AI concepts.
  • Experience working with APIs and integrating external data sources.
  • Background in the insurance industry (including carrier experience) is a plus.

Technical Competencies

  • Data Engineering: Experience building and supporting data warehouses/lakes, especially on Snowflake and Azure.
  • Data Integration: Experience developing ELT/ETL pipelines using modern tools and scripting languages.
  • Data Modeling: Proficient in logical and physical data modeling using relational and dimensional approaches.
  • Performance Optimization: Experience tuning pipelines and database objects for optimal performance.
  • Version Control & CI/CD: Familiarity with ADO YAML Pipelines or GitHub Actions and automated deployment practices.
  • API Integration: Experience implementing and leveraging APIs for data exchange.

Compensation

  • Commensurate with experience
  • Performance-based incentives

Benefits Package

  • 401(k) company match up to 6% eligible upon hire
  • Medical, dental & vision, including company paid Life insurance and long-term disability
  • Health care flexible spending accounts
  • Paid time off
  • Parental & family leave; military leave & pay
  • Employee Referral Incentive
  • Career Development & Continuing Education Assistance

Physical Conditions/Requirements

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions. While performing the duties of this position, the employee is regularly required to talk or hear. The employee frequently is required to use hands or finger, handle, or feel objects, tools or controls. The employee is occasionally required to stand; walk; sit; reach with hands and arms; climb or balance; and stoop, kneel, crouch, or crawl. The employee must occasionally lift and/or move up to 25 pounds. Specific vision abilities required by this position include close vision, distance vision, color vision, peripheral vision, and the ability to adjust focus. The noise level in the work environment is usually moderate.