Python Architect

1. Hands-on Data Engineering : Minimum 5+ yearsof practical experience building production-grade data pipelines using Python and PySpark.

2. Airflow Expertise : Proven track record of designing, deploying, and managing Airflow DAGs in enterprise environments.

3. CI / CD for Data Projects : Ability to build and maintain CI / CD pipelinesfor data engineering workflows, including automated testing and deployment

4. Cloud & Containers : Experience with containerization (Docker and cloud platforms (GCP) for data engineering workloads. Appreciation for twelve-factor design principles

5. Python Fluency : Ability to write object-oriented Python code manage dependencies, and follow industry best practices

6. Version Control : Proficiency with

• Git
• for source code management and collaboration (commits, branching, merging, GitHub / GitLab workflows).

7. Unix / Linux : Strong command-line skills

8. SQL : Solid understanding of SQL for data ingestion and analysis.

9. Collaborative Development : Comfortable with code reviews, pair programming and usingremote collaboration tools effectively.

10. Engineering Mindset : Writes code with an eye for maintainability and testability; excited to build production-grade software

11. Education : Bachelor’s or graduate degree in Computer Science, Data Analytics or related field, or equivalent work experience.