Databricks Engineer - Data Analytics & AI Division
TypeFull-time job
LocationHungary
Posted1 hour ago
The Project
We are looking for a Data Engineer (Databricks) to join our partner's international team. The role focuses on building and optimizing modern data platforms, developing scalable data pipelines, and supporting cloud-based analytics solutions in a dynamic environment.
Requirements
Requirements
Bachelor's degree in Computer Science, Information Technology, or a related field
More than 4 years of experience in data engineering, big data, or cloud-based analytics, with a strong preference for experience in banking or fintech sector
More than 2 years of hands-on experience with Databricks (Workflows, Jobs, Notebooks, and Clusters), including Delta Lake, Spark Structured Streaming
Expertise in Apache Spark (PySpark/Scala) for large-scale data processing and real-time analytics
Advanced experience in SQL and Python/Scala, with experience in data transformations and ETL pipelines
Strong understanding of Delta Lake architecture for data versioning, ACID transactions, and schema evolution
Experience with Cloud Platforms, particularly Databricks on Azure
Knowledge of Lakehouse architecture and designing scalable, secure, and cost-efficient data pipelines is a plus
Familiarity with streaming architectures (Kafka) is a plus
Experience in MLOps and model deployment using MLflow in Databricks is a plus
Ability to collaborate with data scientists, analysts, and business teams to understand data needs
Strong problem-solving skills, with the ability to troubleshoot performance bottlenecks and optimize workloads
Excellent communication skills to explain technical concepts to non-technical stakeholders
Benefits
Benefits
Full-remote working
International working environment
Modern technologies and challenging projects
Opportunity to work with experienced professionals
Long-term career opportunities
Originally posted on Himalayas
We are looking for a Data Engineer (Databricks) to join our partner's international team. The role focuses on building and optimizing modern data platforms, developing scalable data pipelines, and supporting cloud-based analytics solutions in a dynamic environment.
Requirements
Requirements
Bachelor's degree in Computer Science, Information Technology, or a related field
More than 4 years of experience in data engineering, big data, or cloud-based analytics, with a strong preference for experience in banking or fintech sector
More than 2 years of hands-on experience with Databricks (Workflows, Jobs, Notebooks, and Clusters), including Delta Lake, Spark Structured Streaming
Expertise in Apache Spark (PySpark/Scala) for large-scale data processing and real-time analytics
Advanced experience in SQL and Python/Scala, with experience in data transformations and ETL pipelines
Strong understanding of Delta Lake architecture for data versioning, ACID transactions, and schema evolution
Experience with Cloud Platforms, particularly Databricks on Azure
Knowledge of Lakehouse architecture and designing scalable, secure, and cost-efficient data pipelines is a plus
Familiarity with streaming architectures (Kafka) is a plus
Experience in MLOps and model deployment using MLflow in Databricks is a plus
Ability to collaborate with data scientists, analysts, and business teams to understand data needs
Strong problem-solving skills, with the ability to troubleshoot performance bottlenecks and optimize workloads
Excellent communication skills to explain technical concepts to non-technical stakeholders
Benefits
Benefits
Full-remote working
International working environment
Modern technologies and challenging projects
Opportunity to work with experienced professionals
Long-term career opportunities
Originally posted on Himalayas
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