Cloud Data Engineer

Responsibilities:

• Designed, developed, and maintained ETL integrations using Azure Data Factory, Databricks, and Data Lake for diverse projects including Sales, HR, and Device Usage data
• Led data engineering initiatives by analyzing existing project architecture, optimizing data workflows, and preparing codebases for migration
• Utilized Python, PySpark, and SQL to perform data transformations, ensure data quality, and improve processing efficiency
• Provided technical leadership, directed and coordinated project teams by delegating tasks, mentoring team members, and ensuring high-quality deliverables through best practices and performance monitoring
• Maintained security protocols and access control through Azure Key Vault, and data encryption to ensure compliance with data protection standards
• Managed client and vendor relationships by conducting regular meetings, providing project updates, gathering requirements, and resolving technical issues to meet project milestones

Requirements:

• Proficiency in Python, PySpark, and SQL for large-scale data processing
• Experience with Azure Data Factory, Databricks (or Snowflake), and Azure Data Lake
• Solid understanding of relational and/or NoSQL databases, data modeling, and schema design
• Strong knowledge of ETL/ELT pipelines and data integration practices
• Good communication skills in English (minimum B2 level)
• Proven track record of working in long-term, complex data engineering projects
• Exposure to Data Science and Natural Language Processing (NLP)
• Familiarity with CI/CD pipelines and DevOps practices

Offer:

• Private medical care
• Co-financing for the sports card
• Training & learning opportunities
• Constant support of dedicated consultant
• Employee referral program