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Data Platform Engineer

Posted about 1 month agoViewed

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💎 Seniority level: Lead

📍 Location: United States

🔍 Industry: Advanced analytics consulting

🏢 Company: Tiger Analytics👥 1001-5000AdvertisingConsultingBig DataNewsMachine LearningAnalytics

🪄 Skills: AWSCloud ComputingJavaKubernetesApache KafkaData engineeringScala

Requirements:
  • Proven experience designing and implementing scalable, high-performance data systems in cloud environments.
  • Advanced knowledge of real-time data streaming platforms such as Apache Kafka and AWS Kinesis.
  • Expertise in working with AWS for cloud-based data solutions.
  • Proficiency in Databricks for big data processing and managing data pipelines.
  • Strong hands-on experience with Scala and Java for developing data-intensive applications.
  • Familiarity with Apache Spark for distributed data processing.
  • Experience with Kubernetes or other orchestration frameworks.
  • Experience writing infrastructure as code.
Responsibilities:
  • Lead the solution design and implementation of end-to-end data pipelines that support real-time streaming and integration across multiple platforms.
  • Manage and mentor a team of engineers, providing guidance on technical approaches and troubleshooting.
  • Drive modernization efforts for existing data platforms with cloud-native technologies.
  • Design and implement robust streaming data pipelines using technologies like Apache Kafka and Kinesis.
  • Identify bottlenecks in data workflows to improve performance and increase throughput.
  • Ensure reliability and resilience of the data platform, focusing on monitoring and incident management.
  • Advise and enforce best practices for data management processes and data quality.
  • Collaborate with cross-functional teams to deliver business value.
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