Data Engineer
Data
Work location
Zagreb
Job type
Full-time
Work mode
Hybrid
Seniority level
Mid
Published
24 May 2026
Position description
We are seeking an experienced Data Engineer to join our VIS team. The selected candidate will be responsible for developing and maintaining integration routines and visualizations using technologies such as Spark, SQL, stored procedures, Power BI, and similar tools.
Responsibilities
- Pipeline Engineering: Design, build, and maintain robust batch and real-time data pipelines (ETL/ELT) to unify fragmented data sources.
- Database Optimization: Write, optimize, and maintain advanced SQL queries, stored procedures, and data models for maximum performance.
- Legacy Modernization: Assist in migrating client data architectures from legacy on-premise systems (e.g., SSIS, ODI) to modern cloud environments.
- Collaboration & BI Support: Work closely with front-end teams to prepare and structure data for seamless consumption in Power BI dashboards and AI models.
- End-to-End Ownership: Take full responsibility for your data pipelines—from initial ingestion and data cleansing to final orchestration and validation.
Requirements
- Experience: 2+ years of proven experience in a Data Engineering or similar data-focused technical role.
- Education: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or a related technical field.
- Core Technical Stack: Advanced proficiency in SQL and hands-on experience with at least one major integration/transformation technology (e.g., PySpark, dbt, MS SSIS, Oracle Data Integrator).
- Scripting & Analytics: Strong foundational knowledge of Python and familiarity with Power BI or similar data visualization tools.
- Work Style & Presence: A strong sense of personal responsibility, initiative, and the ability to drive tasks independently. Willingness to work on-site at our office for the majority of the time to foster team collaboration.
- Languages: Full proficiency in both Croatian and English (written and spoken) for clear internal and client communication.
Bonus qualifications
- Experience with cloud data platforms like Snowflake, Google BigQuery, or AWS.
- Familiarity with data orchestration tools such as Apache Airflow or cloud-native schedulers.
- Understanding of modern data modeling methodologies (e.g., Data Vault, Kimball Star Schema).
- Basic exposure to or interest in Machine Learning pipelines and Agentic AI infrastructure.
What we offer
- Performance Bonuses
- Professional Growth & Training
- Senior Mentorship
- Daily Covered Perks