Rate: depending on experience Work location: MI (hybrid) We are seeking a highly skilled and certified Data Engineer with expertise in Big Data technologies, Kafka, and Google Cloud Platform (GCP). The ideal candidate will have a strong background in designing, building, and maintaining scalable data pipelines, as well as experience with real-time data processing. You will be responsible for ensuring the reliability, efficiency, and scalability of our data infrastructure. Key Responsibilities: + Design, develop, and maintain scalable data pipelines and ETL processes using Big Data technologies. + Implement and manage real-time data streaming solutions using Apache Kafka. + Architect and manage data storage solutions on Google Cloud Platform (GCP), ensuring high availability and reliability. + Collaborate with data scientists, analysts, and other engineering teams to integrate data solutions into various applications. + Optimize data systems and pipelines for performance, scalability, and cost-efficiency. + Ensure data quality and integrity across all data pipelines. + Monitor and troubleshoot data pipelines to ensure continuous and reliable data flow. + Document data engineering processes and maintain comprehensive records of all data infrastructure components. + Stay up to date with the latest trends and best practices in data engineering, Big Data, Kafka, and GCP. Qualifications: Certification: Google Cloud Certified - Professional Data Engineer or equivalent certification. Experience: 3+ years of experience in data engineering with a focus on Big Data technologies. Technical Skills: + Proficiency in Apache Kafka for real-time data streaming. + Hands-on experience with Google Cloud Platform (GCP) services such as BigQuery, Dataflow, Pub/Sub, Cloud Storage, etc. + Strong knowledge of ETL processes and data pipeline orchestration tools. + Experience with distributed data processing frameworks like Apache Hadoop, Apache Spark, etc. + Proficiency in programming languages such as Python, Java, or Scala. + Experience with SQL and NoSQL databases.