Data Engineer

• Develop and execute the organization’s data strategy and architecture aligned with business objectives
• Translate business requirements into scalable data architecture, models and technical specifications
• Design and manage data models, metadata, lineage and data catalogs
• Architect and integrate batch and real-time data pipelines across diverse sources and platforms
• Establish and enforce data governance, quality, security, privacy and regulatory standards
• Design and deploy scalable cloud and hybrid data platforms, optimizing performance and cost
• Implement data profiling, validation, cleansing and lifecycle management processes
• Monitor, troubleshoot and optimize data platforms, pipelines and infrastructure
• Collaborate with business leaders, engineers and data scientists to deliver data solutions
• Lead data architecture initiatives and mentor teams on standards, tools and best practices
• Evaluate emerging data, cloud, big data and AI technologies and recommend relevant solutions
• Provide expert services remotely while integrated into the company team collaborating closely with a major client’s on-site IT team

Data Architect

• Design, develop, and maintain data pipelines to ensure efficient and reliable data processing
• Implement and optimize data models, data storage, and data integration solutions
• Perform data profiling, data cleansing, and data transformation activities
• Monitor and troubleshoot data pipelines to identify and resolve issues in a timely manner

• Design, build, and operate scalable data platforms for marketing products.
• Enable campaign measurement, customer insights, reporting, and AI/ML initiatives.
• Independently design and maintain scalable ETL pipelines delivering clean, analytics- and AI-ready data.
• Develop, optimize, and automate data processes using SQL, Python, PySpark, MS Fabric, Azure Data Factory, Databricks, and Snowflake.
• Design robust ETL processes, scalable data models, and optimized design patterns for analytics and BI workloads.
• Ensure data quality and governance through automated checks, monitoring, source-to-target mapping, data lineage, and continuous improvements.
• Collaborate with Product, Engineering, Data Science, and Business stakeholders to understand requirements and business semantics.
• Troubleshoot, optimize, and support production pipelines.
• Use Git and Agile practices in collaborative, iterative projects.

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows
• Build and optimise cloud-based data solutions using Google Cloud Platform (GCP)
• Design and maintain data models and data processing workflows
• Integrate structured and unstructured data from multiple sources
• Develop batch and real-time data processing solutions
• Ensure high levels of data quality, reliability, availability, and performance
• Monitor, troubleshoot, and optimise data pipelines and production workloads
• Implement automated testing and data validation processes
• Contribute to data architecture and technical design decisions
• Support data warehouse and data lake solutions
• Apply data security, governance, and access-control best practices
• Contribute to CI/CD and automation practices for data solutions
• Collaborate with Data Scientists, Analysts, Architects, and other engineering teams
• Mentor less experienced engineers and contribute to data engineering best practices

Data Engineer jobs in Greece

Data Architect

Data Engineer

Data Engineer

Senior Data Engineer – GCP