data engineer
Jul 24, 2026 · Grant Thornton Greece
What you'll do
- Develop and implement data pipelines using Azure Databricks, Synapse Analytics, Data Factory, and Data Lake Storage Gen2
- Build scalable and reliable ETL/ELT pipelines
- Design and optimize data storage and processing architectures for advanced analytics and machine learning
- Maintain data security and integrity across Azure environments
- Collaborate with team members to follow data architecture standards and strategies
- Assist in adoption of CI/CD pipelines, automation, and infrastructure as code using Azure DevOps
- Work with the data engineering team to deliver high-quality solutions
Key requirements
- 1+ years' experience
- Experience with Azure Databricks, Synapse Analytics, Data Factory, and Data Lake Storage Gen2
- Proficiency in Apache Spark, Python, and SQL for data manipulation and transformation
- Knowledge of data warehousing principles and data modeling techniques
- Experience with ETL/ELT pipelines and CI/CD pipelines using Azure DevOps
- Familiarity with cloud security and data governance standards
- Experience with infrastructure as code and automation workflows
Benefits
- Diverse and inclusive workplace, friendly dynamic environment, competitive salary and bonus, insurance program for all members, fully funded training and professional qualifications, extra days off, corporate sports teams, exclusive discounts, and company car depending on job level.
About the job
We're looking for a skilled Data Engineer to join our AI Center of Excellence. In this role, you'll be a key part of the team, helping to design and build the data solutions that power our AI and machine learning initiatives. You will work on our modern data platforms built on Azure and help implement data solutions that enable data-driven decisions. This is an exciting opportunity to work with cutting-edge tools and talented professionals to solve complex data challenges.
The key responsibilities of this role will include:
Develop and implement data pipelines using technologies like Azure Databricks, Synapse Analytics, Data Factory, and Data Lake Storage Gen2
Build scalable and reliable ETL/ELT pipelines
Design and optimize data storage and processing architectures for advanced analytics and machine learning
Help maintain data security and integrity across our Azure environments
Collaborate with other team members to follow data architecture standards and strategies
Assist in the adoption of CI/CD pipelines, automation, and infrastructure as code using Azure DevOps
Work with the data engineering team to deliver high-quality solutions
To be successful at this role you need the following (hard and soft skills):
At least 1+ year of experience, preferably Azure data stack or similar (e.g., Databricks, Synapse Analytics, Data Factory, and Data Lake Gen2)
Knowledge of big data technologies, particularly Apache Spark
Proficiency in Python and SQL for data manipulation and transformation
A solid understanding of data warehousing principles and data modeling techniques
Experience with CI/CD pipelines and automation workflows using Azure DevOps
Familiarity with cloud security and data governance standards
Strategic thinker with the ability to translate complex data needs into scalable architectural solutions
Effective communicator who can engage both technical and non-technical stakeholders
Passionate about innovation, efficiency, and continuous improvement
An Azure Data Engineer Associate or similar certification is a plus
What’s in it for You?
At Grant Thornton Greece, we believe that great work deserves great rewards! Here’s what you can look forward to:
🌈 Diverse and inclusive workplace
🏋️♂️ Friendly, Dynamic Working environment
💰 Competitive Salary & Bonus
🩺 Insurance Program for all GT members
👩🏫 Fully funded Training & Professional Qualifications
🏖 Extra Days-off: August Freedays, Volunteering Days, Early leave days
🏃🏽♂️ Corporate Sports Teams (e.g., Running, Basketball, Volleyball)
🎁 Exclusive Discounts: Special offers and discounts for employees
🚗 Company Car (depending on job level)




