Junior Data Engineer

The opportunity   

Our EY Consulting ambition is to become the world’s leading transformation consultants, trusted to help our clients generate long-term value. We’re building world-class capabilities in business, technology and people consulting to help us deliver on EY’s purpose of building a better working world - our firm’s broader ambition to become the world’s most trusted, distinctive professional services organization.  

Our clients are at the heart of our new strategy. We’re focused on solving the key issues of our client buyers, building deeper relationships, and making a greater impact. We’re introducing a new go-to-market narrative - Transformation Realized™ - to help us harness the core drivers of transformation that will create long-term value for our clients.   

To achieve this, we are seeking a Junior Data Engineer to join our Transformation Realized™ Consulting practice to support our clients in designing and delivering modern data platforms, building scalable data pipelines, and enabling data-driven decision-making through analytics and business intelligence. Our team is part of EY’s Europe Central (EC) cluster, delivering market leading services to organizations across industries in Cyprus and internationally.    

Key Responsibilities 

• Support the design, development, and maintenance of scalable data pipelines and data architectures  

• Work with modern data platforms, with a strong focus on Databricks or Spark-based solutions  

• Collaborate with data scientists, analysts, and business stakeholders to deliver data-driven solutions  

• Assist in implementing data quality, validation, and governance processes  

• Contribute to code reviews and follow engineering best practices  

• Help document and optimize end-to-end data flows  

• Support the development of ETL/ELT processes for ingesting and transforming data from various sources  

• Participate in learning and applying best practices in cloud-based data engineering 

• Support in designing and rolling out the data architecture and infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources   

Skills and Attributes for Success 

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field 

• 0–2 years of experience (internships or academic projects are relevant) 

• Hands-on or academic experience with Databricks, Apache Spark, or distributed data processing frameworks 

• Basic understanding of data modelling concepts (e.g., star schema, fact/dimension tables) 

• Familiarity with data warehousing concepts and modern data platforms 

• Experience or exposure to SQL and relational databases (e.g., SQL Server, MySQL, PostgreSQL) 

• Exposure to ETL/ELT concepts and tools (e.g., dbt, SSIS, or similar) 

• Willingness to learn cloud platforms (Azure, AWS, or GCP) and modern data engineering practices 

• Ability to work with structured and unstructured datasets 

• Strong problem-solving skills and eagerness to learn 

• Good communication and teamwork skills  

It will be a plus if you have   

• Experience with Databricks (Delta Lake, notebooks, workflows) 

• Exposure to Azure Data Platform (Azure Data Factory, Synapse, ADLS) 

• Knowledge of Python or Scala for data processing 

• Familiarity with version control (e.g., Git) 

• Basic understanding of CI/CD concepts 

• Experience with orchestration tools (e.g., Airflow, Azure Data Factory pipelines) 

• Understanding of agile/lean development methodologies