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Senior Data Engineer / Databricks at High Tech Engineering Center Kft. – Budapest | Jobyssey

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Senior Data Engineer / Databricks

Senior Data Engineer / Databricks

High Tech Engineering Center Kft. · Budapest, Szervita tér . · 1 month ago

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Work mode: Onsite
Seniority: Senior
Category: Data engineering
Experience: 7+ years

airflow analytics automation aws azure cloud cloud-native containerization data-engineering

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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

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