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Databricks Engineer - Data Analytics & AI Division

Key Facts

Remote From: 
Full time
Mid-level (2-5 years)
English

Other Skills

  • Collaboration
  • Problem Solving
  • Communication

Roles & Responsibilities

  • 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
  • More than 2 years of hands-on experience with Databricks (Workflows, Jobs, Notebooks, and Clusters)
  • Expertise in Apache Spark (PySpark/Scala) for large-scale data processing and real-time analytics

Requirements:

  • Building and optimizing modern data platforms
  • Developing scalable data pipelines
  • Supporting cloud-based analytics solutions
  • Collaborating with data scientists, analysts, and business teams to understand data needs

Job description

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


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