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Before you apply, please get familiar with Luxoft Luxoft locations: Logeek Magazine: Luxoft Alumni Club: Responsibilities: Design and implement scalable data pipelines using Databricks and Kafka Build and maintain real-time streaming solutions for high-volume data Collaborate with cross-functional teams to integrate data flows into broader systems Optimize performance and reliability of data processing workflows Ensure data quality, lineage, and compliance across streaming and batch pipelines Participate in agile development processes and contribute to technical documentation Mandatory Skills Description: +5 years of experience in data engineering roles Proven expertise with Databricks (Spark, Delta Lake, notebooks, performance tuning) Strong hands-on experience with Apache Kafka (topics, producers/consumers, schema registry) Solid understanding of streaming frameworks (e.G., Spark Structured Streaming, Flink, or similar) Experience with cloud platforms (AWS, Azure, or GCP) Proficiency in Python or Scala for data pipeline development Familiarity with CI/CD pipelines (GitLab, Jenkins) and agile tools (Jira) Exposure to data lakehouse architectures and best practices Knowledge of data governance, security, and observability Project Description: We are seeking a skilled and hands-on Data Engineer with proven experience in Databricks, Apache Kafka, and real-time data streaming solutions.

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