Data Engineer I

Codoxo is building data platforms that enable analytics, reporting, and machine learning. In this hybrid role in Duluth, GA, the Data Engineer will help shape scalable data pipelines and support reliable delivery of structured and unstructured data for downstream teams. The position works under senior engineers’ guidance, with a focus on ETL/ELT workflows, performance, and data quality.

Responsibilities

• Assist in designing, building, and maintaining scalable ETL/ELT data pipelines.
• Develop and optimize batch and streaming workflows using tools such as AWS Glue, Spark, and Airflow.
• Support data integration across multiple structured and unstructured data sources.
• Write clean, efficient, and maintainable code in Python, PySpark, and SQL.
• Monitor, troubleshoot, and improve pipeline reliability and performance.
• Optimize database performance, particularly in PostgreSQL and cloud environments.
• Maintain and support AWS-based infrastructure, including EC2, S3, and Glue.
• Implement data validation, quality checks, and 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.
• Use AI-assisted development tools to improve development speed, testing coverage, and code quality.

Required Qualifications

• 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 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 work collaboratively in a team environment under mentorship.
• Strong written and verbal communication skills.

Technologies

• Python, PySpark, SQL
• AWS Glue, Spark, Airflow (Apache Airflow)
• PostgreSQL
• EC2, S3, IAM
• Linux
• ETL, ELT, AWS

Benefits

• Health, Dental, and Vision insurance with 100% employee premium coverage (Starts Day 1)
• Unlimited PTO
• Annual Professional Development stipend
• Annual home office stipend
• 401K Match (after 90 days)

Preferred Qualifications

• Experience working with medical claims data 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 (e.g., Git).
• Understanding of data security, governance, and compliance best practices.
• Experience supporting machine learning pipelines or analytics platforms.
• Demonstrated use of AI tools (e.g., code assistants, automation platforms) to improve development efficiency.

Accessibility Notice

If you need reasonable accommodation for any part of the employment process due to a physical or mental disability, please send an email to [email protected] with the subject line.

Location: Duluth, GA (hybrid)