High Tech Engineering Center Kft.
Senior Data Engineer / Databricks
- Compensation
- Not disclosed
- Location
- Budapest, Szervita tér .
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 7+ years
- Category
- Data engineering
- Posted
Skills
Full description
- Ownership of data engineering features, architecture, and code quality
- Design, implementation, and maintenance of Databricks-based data pipelines and workflows
- Building and optimization of ETL/ELT processes using Apache Spark on Databricks
- Design and management of data lakes and Lakehouse architectures (Delta Lake)
- Integration of diverse data sources and ensuring reliable data ingestion
- Automation of orchestration, scheduling, and monitoring of Databricks jobs
- Design and implementation of fault-tolerant and scalable data processing workflows
- Ensuring high data quality, consistency, and accuracy across the platform
- Making informed decisions about storage, compute, and performance optimization
- Collaboration with analytics, BI, and business stakeholders to support data-driven products
- 7+ years of relevant experience as a Data Engineer
- Strong hands-on experience with Databricks and Apache Spark
- Proficiency in Python or Scala
- Very good knowledge of SQL, relational databases, and data warehousing concepts
- Solid experience with ETL/ELT principles and data pipeline design
- Hands-on experience with cloud platforms (Azure, AWS, or GCP), preferably Databricks workloads
- Experience working with distributed systems and large-scale data processing
- Familiarity with Unix-like operating systems
- Experience with version control systems
- Strong communication skills
- English language proficiency
- Databricks certifications - Professional level
- Experience with Delta Lake, performance tuning, and cost optimization
- Experience with streaming technologies (Kafka or similar)
- Knowledge of workflow orchestration tools (Databricks Workflows, Airflow, etc.)
- Experience with cloud-native and serverless data architectures
- Familiarity with containerization and virtualization (Docker, Kubernetes)
- Experience building data assets that directly support analytics and business decision-making