About the role

High Technical Impact: A unique professional challenge to shape the core data platform for a stable, market-leading global enterprise.
Competitive Compensation
Benefits Package: Cafeteria allowance and private health insurance package.
Flexibility: Hybrid working model requiring 2 days of office presence (Budapest) and offering 3 days of Home Office per week.

Translate business questions into reliable data products — from requirements through delivery and iteration
Develop and optimize SQL queries, materialized views, and pre-aggregated summaries to keep dashboard latency and cost in check
Build ETL and ELT processes for ingesting, transforming, and validating data from multiple sources
Build and maintain gold and published-layer datasets for analytics and BI consumption
Partner with analytics and BI teams to prepare curated datasets for embedded analytics (e.g., Omni) and BI dashboards (e.g., Power BI)
Monitor data pipeline health, troubleshoot failures, and implement alerting and observability solutions
Ensure data quality, accuracy, and consistency across all pipeline stages
Participate in code reviews, documentation, and knowledge sharing with the team

Required Qualifications

3-7 years of professional data engineering experience
Strong proficiency in SQL; demonstrated ability to write and optimize complex queries
Hands-on experience with Databricks; working knowledge of Apache Spark fundamentals
Solid understanding of data warehouse and data lake concepts and architecture patterns
Experience designing and implementing ETL/ELT pipelines
Proficiency in at least one programming language (Python, Scala, or similar)
Experience with AWS (or another major cloud) - S3 / object storage, IAM, and secret management
Understanding of data quality, validation, and testing principles
Strong problem-solving skills and ability to work independently with guidance

Preferred Qualifications

Experience implementing medallion architecture patterns (bronze/silver/gold layers)
Familiarity with Delta Lake and its transactional capabilities
Experience preparing data for BI tools (Power BI, embedded analytics like Omni) or creating data models for analytics
Working knowledge of Delta Lake and Delta Live Tables (DLT) — declarative pipelines, expectations, incremental processing
Certification in Databricks for ‘Data Analyst’, ‘Data Engineer’, ‘ML Engineer’
Experience with version control (Git) and CI/CD best practices
Understanding of data governance, metadata management, and data cataloging
Exposure to streaming data and real-time pipeline requirements
Experience optimizing costs in cloud data platforms

Technical Skills

Data engineer