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As a skilled professional in data engineering, you will be responsible for designing and implementing scalable data pipelines using Databricks and Kafka. Mandatory Skills: +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 Responsibilities Include: Building and maintaining real-time streaming solutions for high-volume data Collaborating with cross-functional teams to integrate data flows into broader systems Optimizing performance and reliability of data processing workflows Ensuring data quality, lineage, and compliance across streaming and batch pipelines Participating in agile development processes and contributing to technical documentation Requirements: We are seeking a skilled and hands-on Data Engineer with proven experience in Databricks, Apache Kafka, and real-time data streaming solutions. Project descriptions are available upon request. About This Project: We value collaboration and teamwork as we seek candidates who can communicate effectively with cross-functional teams.
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Data Engineering Excellence Position
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Brazil beBeeImpact Tempo inteiroUnlocking Entrepreneurial Potential: A Revolutionary Role About the Opportunity: This is a high-ownership, high-velocity engineering role where you'll build new tools and experiences that give entrepreneurs real leverage. As a senior full-stack engineer on our product and AI team, you'll integrate AI into user-facing flows — conversational builders,...