Junior Data Engineer

Cloudfide builds cloud-native data platforms, processes massive datasets, and works with international clients including Fortune 500 and leading retail organizations. The company focuses on Big Data, AI/ML, Databricks, and advanced data lakehouse architectures.

• Minimum 6 months of commercial experience related to data engineering or a closely related technical data role.
• Hands-on experience with data-related work (e.g., data transformation, SQL development, ETL, cloud tools, scripting).
• Familiarity with at least one cloud platform, Azure preferred; AWS/GCP also welcome.
• Knowledge of Python for data processing tasks.
• Solid understanding of SQL and relational databases.
• General awareness of data modeling, ETL/ELT concepts, and cloud environments.
• Curiosity, willingness to learn, and openness to working in dynamic, evolving data projects.
• Strong communication, problem-solving attitude, and a proactive mindset.

Nice to Have:

• Exposure to Databricks, Spark, or PySpark.
• Familiarity with Airflow or other orchestration tools.
• Experience with CI/CD (Azure DevOps, GitHub Actions).
• Any experience in cloud-based analytics or data pipelines.

• Assisting in building and maintaining data pipelines and data models in cloud environments (Azure is the main stack).
• Supporting the implementation of data engineering best practices (quality checks, documentation, testing, monitoring).
• Working with senior engineers on tasks related to data transformation, processing, and optimization.
• Participating in discussions with clients and internal teams to understand requirements.
• Contributing to the development of robust, scalable cloud data solutions.
• Learning continuously - new technologies, cloud services, frameworks, and project methodologies.

Cloudfide is an Equal Opportunity Employer committed to creating an inclusive environment for all employees.