Data Engineer

Codoxo is seeking a Data Engineer to design, build, and maintain scalable data pipelines that power analytics, reporting, and machine learning initiatives. This onsite role in Duluth, Georgia reports to senior engineers and expects a strong foundation in data engineering practices combined with collaboration across teams.

Responsibilities

• Assist in designing, building, and maintaining scalable ETL and ELT data pipelines.
• Develop and optimize batch and streaming workflows using AWS Glue, Spark, and Airflow.
• Support data integration across multiple structured and unstructured sources.
• Write clean, efficient, and maintainable code in Python, PySpark, and SQL.
• Monitor, troubleshoot, and improve the reliability and performance of data pipelines.
• Optimize database performance, with a focus on PostgreSQL and cloud-based environments.
• Maintain and support AWS-based infrastructure including EC2, S3, and Glue.
• Implement data validation, quality checks, and ongoing monitoring processes.
• Ensure compliance with data governance, security, and regulatory standards.
• Collaborate with data scientists and analysts to translate data requirements into scalable engineering solutions.
• Document data flows, architecture decisions, and technical processes.
• Leverage AI-assisted development tools to enhance speed, testing coverage, and code quality.

Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field, or equivalent practical experience.
• 2+ years of experience in data engineering, software engineering, or related technical roles (internships included).
• Proficiency in Python, PySpark, and SQL.
• Familiarity with ETL/ELT concepts and data pipeline architecture.
• Experience working with relational databases such as PostgreSQL.
• Basic understanding of cloud computing concepts, preferably AWS.
• Exposure to distributed data processing frameworks such as Spark.
• Experience working in Linux environments and basic shell scripting.
• Strong analytical and problem-solving skills.
• Ability to collaborate effectively in a team environment under mentorship.
• Strong written and verbal communication skills.

Technologies

• Python
• PySpark
• SQL
• AWS
• AWS Glue
• Spark
• Airflow
• PostgreSQL
• Linux
• Shell scripting
• Git

Benefits

• Health, Dental, and Vision insurance with 100% employee premium coverage (Starts Day 1)
• Unlimited paid time off
• Annual professional development stipend
• Annual home office stipend
• 401K match after 90 days

Preferred Qualifications

• Experience working with medical claims data is strongly preferred.
• Hands-on experience with AWS services such as EC2, S3, Glue, and IAM.
• Experience with workflow orchestration tools such as Apache Airflow.
• Exposure to data warehousing concepts and dimensional modeling.
• Familiarity with CI/CD pipelines and version control (eg, Git).
• Understanding of data security, governance, and compliance best practices.
• Experience supporting machine learning pipelines or analytics platforms.
• Demonstrated use of AI tools to improve development efficiency.
• Physical requirements: work is performed in an office environment (office or remote) and requires computer use, standard office equipment operation, and desk work.