Junior Data Engineer

Barry Callebaut Digital (BC Digital) aims to lead the digital transformation in the chocolate industry. As a Junior Data Engineer, you will join the
central Data Engineering team to support the development and operation of scalable and reliable data pipelines. This role is ideal for early-career
professionals looking to build strong foundations in data platforms, cloud technologies, and analytics engineering, while collaborating with
experienced engineers, analysts, and architects. You will focus on ensuring data is available, accurate, and well-structured for analytics, reporting,
and AI use cases.

MAIN RESPONSIBILITIES & SCOPE
Data Pipeline Development
 Build and maintain ETL / ELT data pipelines to ingest and transform data from internal and external source systems
 Support data ingestion using Microsoft Fabric, Azure Data Services, and cloud-based data platforms
 Implement data transformations using SQL, Python, notebooks, or Spark-based tools under guidance from senior engineers
 Assist with integrating structured and semi-structured data into the Lakehouse / Data Lake environment
Data Quality & Reliability
 Apply basic data quality checks and validation rules to ensure accuracy and consistency
 Monitor pipeline execution and help resolve data issues or failures
 Support root-cause analysis for data incidents and contribute to continuous improvement
Platform & Performance Support
 Assist in managing datasets in Azure Data Lake Storage (ADLS) and Microsoft Fabric Lakehouse
 Help optimize data models and queries for analytics and reporting use cases
 Learn and apply basic performance concepts such as partitioning and incremental loading
Collaboration & Documentation
 Work closely with senior data engineers, data analysts, and data scientists to understand data requirements
 Contribute to technical documentation, data models, and pipeline descriptions
 Follow established engineering standards, best practices, and governance guidelines
Learning & Development
 Actively learn modern data engineering tools, frameworks, and ways of working
 Participate in code reviews, team knowledge sharing, and community sessions
Scope:
 Supports multiple business functions and domains across Barry Callebaut
 Works within a global, distributed data and analytics organization

EDUCATION, LANGUAGE, SKILLS & QUALIFICATIONS
 Bachelor’s degree in Computer Science, Engineering, Data, Information

 Proficiency in English (written and spoken)

Section 2 - CANDIDATE PROFILE
ESSENTIAL EXPERIENCE & KNOWLEDGE / TECHNICAL OR FUNCTIONAL COMPETENCIES
 2–4years of experience (or strong academic / internship experience) in data engineering, analytics engineering, or software
engineering
 Basic understanding of data engineering concepts:
 ETL / ELT pipelines
 Data lakes and data warehouses
 Structured vs semi-structured data
 Hands-on experience with SQL
 Basic programming skills in Python (or willingness to learn quickly)
 Familiarity with cloud data platforms (Azure preferred) through coursework, projects, or internships
 Exposure to tools such as Microsoft Fabric, Azure Data Factory, Synapse, Databricks, or Spark is a plus (not mandatory)
 Understanding of version control concepts (e.g. Git) and collaborative development practices
PERSONAL ATTRIBUTES AND WAYS OF WORKING
The ideal candidate…
 Curious and eager to learn new technologies and data concepts
 Structured and detail-oriented approach to problem solving
 Comfortable asking questions and learning from more experienced team members
 Collaborative team player who communicates clearly with technical and non-technical stakeholders
 Takes ownership of assigned tasks and follows through reliably
ADDITIONAL COMMENTS / CONTEXT OF THE ROLE
 This role is part of the Barry Callebaut Data & Analytics organization, led by the CDAO
 The position offers strong learning opportunities in cloud data platforms, analytics, and AI-ready data foundations
 Clear progression paths toward Data Engineer, Analytics Engineer, or Platform Engineer roles