Data Engineer

• Collect and analyze business requirements; define robust data models and scalable architectures.
• Design and build scalable, reliable data pipelines and workflows in cloud environments.
• Apply DevOps practices, including Git-based version control and participation in CI/CD pipelines.
• Ensure data quality, security, and governance standards are maintained across all data-related activities.
• Collaborate with cross-functional teams to align data solutions with business needs and quality expectations.
• Specify and design presentation interfaces with optimal usability and user experience.
• Document processes and tasks to ensure transparency, explainability, and team-wide understanding.
• Support the integration of AI-based enrichment and transformation processes into existing data pipelines and workflows.

Do you have experience in Usability?, Do you have a Master's degree?, * Master's degree in IT with minimum 11 years of relevant experience (or Bachelor's degree and minimum of 15 years relevant experience).

• Εxcellent knowledge in Python, Spark and SQL.
• Εxcellent knowledge in designing and building ETL pipelines using tools such as Azure Synapse, Microsoft Fabric and/or AWS Glue.
• Εxcellent knowledge of data modelling and database design principles using the Medallion Architecture.
• Good knowledge of business intelligence tools, notably Microsoft Power BI.
• Knowledge of Machine Learning, Natural Language Processing and Large Language Models (LLMs) fundamentals.
• Ability to integrate AI and ML techniques into data workflows for enrichment, categorisation and transformation.
• Strong, hands-on coding ability for data processing, analytics, and automation.
• Ability to collect, analyse and translate business needs into technical specifications.
• Skills in designing conceptual, logical and physical data models.
• Ability to extract, transform, load, clean and merge datasets from multiple sources.
• Experience with automated workflows and orchestration tools.
• Ability to handle large and complex datasets efficiently.
• Desirable

• Understanding of Microsoft Power Platform (e.g., Power Automate, SharePoint Lists).
• Good knowledge of Microsoft Fabric components, including Lakehouses, Pipelines, Dataflows Gen2, Notebooks, and Semantic Models.
• Good knowledge of cloud environments (AWS or Microsoft Azure).
• Understanding of DevOps practices, including Git workflows and CI/CD pipelines, with experience using tools such as Azure DevOps, GitHub, and GitLab.
• Knowledge of no-code/low-code data science platforms such as KNIME and/or Dataiku.
• Experience documenting and organizing processes using task management tools (e.g., Jira, OpenProject) and documentation platforms (e.g., Confluence, GitLab Wiki, GitHub Wiki).

• Proficiency in English at least at level B2.