Senior Python Engineer with GCP

YourITeams is an IT product and service company, founded in 2022, employing between 51 and 200 employees.

• Minimum 6–7 years of commercial software engineering experience.
• Strong Python backend development experience and proven delivery of backend services.
• Hands-on experience with Pydantic, including models, validators, settings management and type enforcement.
• Solid knowledge of designing, implementing and consuming REST APIs; GraphQL is a plus.
• Substantial experience with Apache Airflow, including DAG design, operators, sensors, hooks and XCom usage.
• Experience deploying and operating workflows in Google Cloud Composer.
• Strong understanding of GCP concepts and practical experience with BigQuery, GCS, Pub/Sub, IAM and Cloud Functions.
• Familiarity with API authentication standards such as OAuth2, JWT and API keys.
• Proficiency in SQL for data access and validation tasks.
• Experience with Git, CI/CD pipelines and Docker-based development workflows.

Nice to have:

• Experience with GraphQL.
• Advanced data engineering experience with production-scale pipelines.
• Proven track record building reusable Airflow operators, hooks and utilities.
• Experience designing cloud-native backend architectures at scale.

• Design, implement and maintain Apache Airflow DAGs for data orchestration and automation.
• Manage and optimize GCP Cloud Composer environments and related configurations.
• Develop robust backend services and REST APIs using Python and appropriate frameworks.
• Develop and consume REST APIs; GraphQL experience is an advantage.
• Use Pydantic for schema definition, data validation, type safety and consistency across services and Airflow tasks.
• Integrate pipelines and services through API interactions, ensuring authentication, retries, idempotency and standardized response handling.
• Develop reusable Airflow components such as operators, hooks and utilities.
• Work with GCP services including BigQuery, Google Cloud Storage, Pub/Sub, IAM, and Cloud Functions.
• Implement logging, monitoring, alerting and automated testing for reliable pipeline execution.
• Collaborate with data engineering, platform and product teams to deliver end-to-end solutions.
• Troubleshoot production incidents and implement fixes.