Junior Data Engineer

Our Story In July 2019, Fourth joined forces with Hot Schedules to become the global leader in end-to-end restaurant and hospitality management technology solutions. Together, the merged company now represents the world’s largest and only provider of end-to-end restaurant and hospitality management solutions for customers across the globe and of all sizes, from a single location or franchisee restaurant to a global restaurant or hotel chain.

The combined company’s complete software-as-service (SaaS) solution suite including scheduling, time & attendance, applicant tracking, training, inventory management / procurement, HR / benefits and payroll services now serves customers in 120,000 locations worldwide and is supported by a dedicated, unified team across offices in the US, UK, Bulgaria, China, Australia, and UAE. Interested in joining our smart, fun, and talented team?

Fourth is looking for a Junior Data Engineer to join our Enterprise Data & Intelligence team in Sofia.

As a Junior Data Engineer on the Enterprise Data & Intelligence team, you will learn to design, build, and maintain the data pipelines that underpin Fourth's single source of truth. Working closely under the guidance of the Senior Data Engineer, you will take on well-scoped pipeline and data modelling tasks, build your skills in our Azure-based cloud platform, and grow into a fully independent Data Engineer.

What You’ll Be Working OnGuided Pipeline Development
• Build and maintain scalable ETL/ELT pipeline components (batch) on Microsoft Fabric and Azure Data Factory, under the direction of the Senior Data Engineer.
• Write clean, well-documented T-SQL and Python/PySpark for clearly scoped tasks, following team coding standards.
• Contribute to Bronze and Silver layers builds within the Medallion Architecture, with review before anything reaches production.

Data Quality & Documentation
• Write and run basic data validation and automated tests for the pipelines you build.
• Document your own work as you go: naming, lineage notes, and README-level context, so nothing you build becomes a knowledge silo.
• Flag data quality issues you encounter rather than silently working around them.

Learning & Collaboration
• Work alongside Data Analysts to understand how pipeline output is consumed downstream.
• Ask for and act on code review feedback; treat review comments as the primary mechanism for skill growth in this role.
• Participate in team standards discussions so you learn the reason behind conventions, not just the conventions.

Growth Toward Independence
• Progressively take on larger, less-scoped pieces of pipeline work as competence is demonstrated.
• Build working proficiency with Git-based version control and CI/CD basics for data assets.
• Use AI-assisted development tools (e.g. Copilot, Claude) to accelerate learning and delivery, under guidance on when to trust and when to verify their output.

What We’re Looking For:

This role is suitable for early-career professionals, or candidates with up to 2 years of experience in data engineering, software engineering, internships, academic projects, or relevant personal projects. A degree in Computer Science, Data Engineering, Software Engineering, Mathematics, or a related field is preferred, but equivalent demonstrable experience will also be considered.

Technical Skills
• Working knowledge of SQL (T-SQL preferred) and Python
• Basic understanding of relational databases and data modelling concepts.
• Exposure to cloud platforms (Azure preferred) through coursework, personal projects, or prior internships.
• Familiarity with Git or another version control system.

Soft Skills
• Comfortable asking questions and surfacing uncertainty rather than guessing silently.
• Good documentation instincts and…