Data Scientist

📋 Description

• Data Engineering Expertise: Proven experience in architecting and delivering large-scale
• Advanced Knowledge in Databricks and Snowflake: Hands-on experience in Databricks, Spark, Pyspark
• MLOps Skills: Practical experience in MLOps, ideally with MLflow for model management and deployment
• Cloud Proficiency: Strong knowledge of AWS, with additional experience in Azure advantageous for
• Programming Proficiency: Advanced coding abilities in Python, SQL and Scala
• Tooling Competence: Familiarity with version control (GitHub), CI/CD tools (Azure DevOps, GitHub

🎯 Requirements

• At least 5 years of experience in Data Engineering or a related field
• A minimum of 1 years of hands-on experience with Databricks in a production environment
• Strong expertise in cloud platforms (e.g. AWS, Azure, GCP), Data Lake technologies and Data
• Experience with data ETL tools and BI solutions (e.g., Airflow, PowerBI)
• Experience with data quality and governance tools (e.g., Atlan, Monte Carlo)
• Solid knowledge of data modelling concepts

🎁 Benefits

• An opportunity to join a fast-growing company
• Options for career advancement
• Learning and development opportunities
• Flexible working environment
• Competitive salaries based on experience