Állás részletei
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Cég neve
High Tech Engineering Center Kft.
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Munkavégzés helye
1052, Budapest, Szervita tér 8. -
Munkaidő, foglalkoztatás jellege
- Alkalmazotti jogviszony
- Általános munkarend
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Elvárt technológiák
- BI AWS AZURE SQL PYTHON APACHE ANALYTICS CLOUD DOCKER SPARK DATABASES UNIX VIRTUALIZATION
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Elvárások
- Angol középfok
- 5-10 év tapasztalat
- Középiskola
Kis türelmet...
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Állás leírása
Responsibilities
- 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
- Decision making about storage, compute, and performance optimization
- Collaboration with analytics, BI, and business stakeholders to support data-driven products
Requirements
- 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
Nice-to-have
- 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
How to apply
You can submit your application on the company's website, which you can access by clicking the „Apply on company page“ button.
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