Junior Data Engineer

• Assist in translating legacy ETL processes into modern ELT pipelines using dbt
• Support the development of Data Vault 2.0 models
• Build and maintain data transformations and curated datasets
• Contribute to data integration and migration activities
• Support workflow development using Dagster
• Assist in deploying and monitoring workloads on Open Shift / Kubernetes
• Participate in pipeline monitoring and operational support
• Help implement automated data validation and testing
• Support reconciliation between legacy and modern platforms
• Investigate and resolve data quality issues together with senior team members
• Document technical solutions and operational procedures
• Learn and apply software engineering best practices
• Contribute ideas for improving performance and maintainability
• Participate in code reviews and team knowledge sharing

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field (or equivalent practical experience)
• Up to 3 years of experience in Data Engineering, Business Intelligence, Database Development, or Software Engineering
• Internship or university project experience is also considered
• Experience with some of the following technologies is desirable:
• SQL and relational databases (SQL Server is a plus)
• Basic understanding of Python
• Familiarity with dbt is an advantage
• Understanding of data modelling concepts
• Basic knowledge of Git version control
• Interest in cloud platforms, Kubernetes or Open Shift
• Exposure to ETL / ELT concepts
• Strong willingness to learn new technologies
• Analytical thinking and problem-solving mindset
• Structured and detail-oriented
• Team player with good communication skills
• Motivated to develop within a modern Data Engineering environment
• Basic knowledge of Data Vault concepts
• Familiarity with Kafka or event-driven architectures
• Exposure to Docker or Kubernetes
• Experience with CI/CD concepts
• Interest in financial services or banking environments

Demonstrates expertise in Data Engineering with a focus on modern ELT pipelines, data transformation, and data quality assurance. Proficient in utilizing tools like dbt, SQL, and cloud platforms such as Kubernetes and Open Shift to enhance data integration and operational efficiency.

• Data Engineering
• ELT Pipeline Development
• SQL and Relational Databases
• Dbt Familiarity
• Kubernetes or Open Shift

• SQL
• Data Vault 2.0
• Python
• Data Modelling
• Git Version Control
• ETL / ELT Concepts
• CI/CD Concepts
• Data Transformation
• Automated Data Validation
• Data Quality Assurance

• Analytical Thinking
• Problem-Solving Mindset
• Detail-Oriented
• Team Player
• Good Communication Skills

• Financial Services
• Banking Environments

• Dbt
• Kubernetes
• Open Shift
• Docker
• Dagster
• Kafka