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. 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 Languages: English: C1 Advanced