Build production-grade data systems by writing clean, modular, well-tested Python code for data pipelines and platform services.
Design and maintain data models aligned with medallion architectures (bronze/silver/gold).
Build and maintain data workflows using Dagster (preferred) or Airflow.
Implement idempotent transformation logic using SQLMesh/Tobiko (preferred) or dbt.
Build, debug, and optimize Docker images for local and production environments.
Read and modify infrastructure-as-code using Terraform.
Document data flows, system architecture, and operational procedures clearly.

Requirements

2–4 years of experience in Data Engineering or Backend Software Engineering
Strong proficiency in Python and SQL
Solid understanding of relational theory and data modeling
Experience working with orchestration tools (Dagster, Airflow, or similar)
Familiarity with containerization and Docker-based workflows
Experience working with version control, CI/CD, and collaborative development practices
Ability to write clear technical documentation.

Benefits

📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonSQLdata modelingDagsterAirflowDockerTerraformSQLMeshTobikodbt

Soft Skills

technical documentationcollaborative development