Data Engineer (Junior to Mid level)

We are looking for a Data Engineer who will assist our high-calibre, financial services insurance clients to get useful insights from their data. This position is an excellent opportunity for a person who is passionate about data and analytics to participate in exciting projects and start or advance her/his career in the field.

ImprovIT is a niche technology consulting company providing services for the Insurance, sector, aiming to bridge the gap between Business and IT. Our services span solution implementation and systems integration, data warehouses/data marts and reporting/analytics, software development, enterprise architecture, business analysis, technical project management and insurance technology consulting.

A day in the life of the Data Engineer includes

• Data Discovery and Extraction from multiple sources (transactional systems, files,
• online sources etc.)
• Development of Data Pipelines
• Data Transformation and Cleansing
• Data Model Design in collaboration with data architects
• Requirements Analysis in collaboration with business analysts
• Data Analysis, Visualization , and Reporting

Must have

• Bachelor's degree in Computer Science, Engineering, or other numerate disciplines, ideally combined with a post-graduate level degree.
• Advanced numerical and analytical skills coupled with the desire to study and learn business domains in depth
• Good command of at least one programming language like Python, Java, C# or any other modern language
• Familiarity with at least one DBMS (SQL Server, MySQL, SAP HANA, Oracle, PostgreSQL., etc.)
• Acquaintance with ETL tools like SSIS, Data Factory, Informatica, Talend, SAP BW or similar
• Familiarity with Data Visualization and Analysis tools like PowerBI, Tableau, Qlik, SAP Analytics Cloud or similar
• Excellent command of English and Greek
• For Junior Candidates: 1+ years of professional experience (or strong relevant internships/projects), a solid grasp of data engineering fundamentals and eagerness to learn
• For Mid-level Candidates: 2-4 years of hands-on data engineering experience, proven ability to independently build and monitor production data pipelines and experience optimizing data workflows

Nice to have

• Familiarity with cloud Data Stacks (Azure, AWS, Snowflake, etc.)
• Machine Learning and AI Concepts
• Excellent remuneration package
• Private Life and Health Insurance Plan
• Comprehensive training programs
• A stimulating multi-national working environment and a great business culture!

Great career advancement opportunities