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Junior Data Engineer: ELT Pipelines & Cloud Data Quality

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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 OpenShift / 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

Requirements

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 OpenShift

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

Core Competencies

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 OpenShift to enhance data integration and operational efficiency.

Highest-signal resume keywords

Data Engineering

ELT Pipeline Development

SQL and Relational Databases

Dbt Familiarity

Kubernetes or OpenShift

ATS Optimization Keywords

Hard Skills

Data Vault 2.0

Python

Data Modelling

Git Version Control

ETL / ELT Concepts

CI/CD Concepts

Data Transformation

Automated Data Validation
Data Quality Assurance

Soft Skills

Analytical Thinking

Problem-Solving Mindset

Detail-Oriented

Team Player

Good Communication Skills

Industry Keywords

Financial Services

Banking Environments

Tools & Technologies

Kubernetes

OpenShift

Docker

Dagster

Kafka