Data Engineer: Scalable Pipelines & Azure Cloud

Coca-Cola HBC; Atlanta (GA); On-site; USD 93,000 - 123,000; Full time

Job summary

The Coca-Cola Company is seeking a Data Engineer to design, build, and maintain scalable data solutions that power analytics, reporting, machine learning, and data-driven decision-making. You will work closely with Product, Analytics, Data Science, and Engineering teams to develop trusted datasets and reliable data platforms.

You will help transform raw data into high-quality, actionable information while ensuring performance, quality, governance, and operational excellence in a fast-paced

Qualifications

• Bachelor's degree in computer science, engineering, information systems, or a related field.
• 3+ years of experience in Data Engineering, Analytics Engineering, Software Engineering, or related disciplines.
• Proficiency in Python and SQL, with familiarity in Java or other backend languages.

Responsibilities

• Design, build, and maintain scalable data pipelines, data models, and data products using Python, SQL, Java and cloud-native patterns.
• Apply coding standards, automated testing, version control, CI/CD, and code reviews to data engineering solutions.
• Build and deploy data workloads on Azure platforms such as ADLS, ADF, Synapse, Databricks, and Microsoft Fabric.
• Implement monitoring, logging, alerting, and operational controls to keep pipelines healthy in production.
• Collaborate with platform teams to improve tooling, automation, and observability.
• Partner with Product Managers, Analysts, Data Scientists, and Engineers to deliver business value.

Skills

Python

SQL

Java

Data pipelines

Data modeling

Education

Bachelor’s degree in CS/Engineering/IS

Tools

Azure Data Services

Azure Data Factory

Azure Synapse

Databricks

Git CI/CD

Job description

The Coca-Cola Company is seeking a Data Engineer to design, build, and maintain scalable data solutions that power analytics, reporting, machine learning, and data-driven decision-making. You will work closely with Product, Analytics, Data Science, and Engineering teams to develop trusted datasets and reliable data platforms.

You will help transform raw data into high-quality, actionable information while ensuring performance, quality, governance, and operational excellence in a fast-paced