Data Platform Engineer

About the Company

We are a large-scale consumer technology platform serving millions of users, focused on building data-driven, high-impact products. Our engineering teams work with modern cloud and big data technologies to solve complex, real-world problems at scale.

Roles & Responsibilities

• Design, develop, and maintain real-time and batch data pipelines to support analytics and business use cases.
• Build scalable data processing solutions using Python, Java, or Go .
• Implement and optimize streaming and batch workflows using Spark, Flink, and Kafka .
• Manage and optimize data storage solutions such as ClickHouse and Iceberg .
• Deploy, monitor, and maintain data services using Kubernetes and AWS ECS .
• Ensure data reliability, performance, and quality across data pipelines.
• Perform root cause analysis and troubleshoot data pipeline and production issues.
• Collaborate with cross-functional teams including engineering, analytics, and product.
• Contribute to improving data engineering standards, tools, and best practices.
• (Optional) Support AI/ML-driven use cases such as automated PII detection and anomaly analysis.

Experience and Qualifications

• Bachelors degree in Computer Science, Engineering, or a related field .
• 2+ years of experience in data engineering or backend data systems (experience level can be adjusted).
• Strong programming skills in Python, Java, or Go .
• Hands-on experience with real-time and batch data pipelines .
• Practical knowledge of Spark, Flink, and Kafka .
• Experience working with modern data stores such as ClickHouse and Iceberg .
• Familiarity with cloud-native deployments , including Kubernetes and AWS ECS .
• Strong problem-solving, debugging, and troubleshooting skills.
• Ability to work effectively in a collaborative, fast-paced environment .
• Excellent verbal and written communication skills.