Java Software Engineer

Coca-Cola • Atlanta, GA

1d

About The Position

The role is described as a Data Engineer responsible for designing, building, and maintaining scalable data solutions that support analytics, reporting, machine learning, and data-driven decision-making. The engineer will work with Product, Analytics, Data Science, and Engineering teams to develop trusted datasets, reliable data pipelines, and scalable data platforms, transforming raw data into high-quality, actionable information while ensuring performance, quality, governance, and operational excellence.

The position involves developing data pipelines, data models, and data products using Java, Python, SQL, and cloud-native engineering patterns. It also includes delivering workloads on Azure services, supporting production operations through automation and observability, and contributing to engineering standards, design reviews, and documentation. The role is based in Atlanta, United States, with 0%–25% travel required and no relocation provided. The Coca-Cola Company will not sponsor employment-based visas for this position; applicants must already be authorized to work full-time in the United States without sponsorship.

Requirements

• Bachelor’s degree in computer science, Engineering, Information Systems, or a related field.
• At least 3 years of experience in Data Engineering, Analytics Engineering, Software Engineering, or related disciplines.
• Strong proficiency in Python and SQL.
• Proven experience building batch and streaming data pipelines, transformation frameworks, data models, and reusable data engineering components.
• Hands-on experience with Azure data services such as ADLS, Azure Data Factory, Synapse, Databricks, Microsoft Fabric, or equivalent cloud data platforms.
• Strong understanding of design patterns, modular coding, error handling, automated testing, CI/CD, Git-based workflows, and production-grade engineering practices.
• Experience implementing data validation, monitoring, logging, lineage, and alerting for trusted and reliable data products.
• Familiarity with Git, CI/CD pipelines, containerization concepts, and deployment automation for data engineering workloads.
• Must be currently authorized to work full-time in the United States and must not require the company's sponsorship to continue working legally in the United States.

Nice To Haves

• Familiarity with Java or other backend programming languages.
• Experience with Azure Synapse, Databricks, Snowflake, BigQuery, Redshift, or similar platforms.
• Experience with orchestration tools such as Airflow, Synapse Pipelines, Dagster, or dbt.
• Familiarity with CI/CD, Infrastructure as Code, and DevOps practices.
• Experience supporting machine learning workflows through feature engineering and training data preparation.
• Exposure to data observability, monitoring, testing, and governance tools.
• Knowledge of event-driven architecture and real-time data processing.
• Azure Data Engineer certification or equivalent cloud certification.
• Strong ownership and accountability.
• Advocacy for data quality, reliability, and trust.
• Effective communication with technical and non-technical stakeholders.
• Ability to balance technical excellence with practical business outcomes.
• Ability to thrive in a collaborative, agile environment.
• Interest in continuous learning and process improvement.

Responsibilities

• Design, build, and maintain scalable data pipelines, data models, and data products.
• Use Java, Python, SQL, and cloud-native data engineering patterns to develop data solutions.
• Build and deploy data workloads on Azure platforms, including ADLS, Azure Data Factory, Synapse, Databricks, and Microsoft Fabric, as applicable.
• Apply coding standards, modular design, automated testing, version control, CI/CD, and code review practices.
• Implement deployment automation, monitoring, logging, alerting, and operational controls to maintain stable production data pipelines and services.
• Collaborate with platform teams to improve tooling, automation, CI/CD, monitoring, and observability.
• Use version control and software engineering best practices to maintain high-quality code.
• Partner with Product Managers, Analysts, Data Scientists, and Software Engineers to deliver business value.
• Contribute to data engineering standards, design reviews, and documentation.
• Identify opportunities to improve reliability, scalability, and efficiency across the data ecosystem.

Benefits

• A full range of medical, financial, and/or other benefits, dependent on the position.
• Annual incentive reference value of 7.5%.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level