Junior Data Engineer

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.

• 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.

• 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.

• 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.

• 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.

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.

• 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.

• Comfortable asking questions and surfacing uncertainty rather than guessing silently.
• Good documentation instincts and a willingness to write things down.
• Proactive and timely communication on progress and blockers.
• Proficiency in English, both spoken and written.

• Exposure to Microsoft Fabric, Azure Data Factory, or Synapse.
• Familiarity with dbt or another transformation framework.
• Exposure to tools like Apache NiFi, Fivetran, Boomi, etc.
• Basic exposure to Power BI or another BI tool.
• Personal projects, coursework, or internship experience…