Data Ingestion SRE, Data Platform

• End-to-End Service Lifecycle Management: Participate in and continuously improve the full lifecycle of services, from initial design and development to deployment, ongoing operation, and iterative optimization.
• Ensure Reliability and Scalability: Maintain highly reliable, fault-tolerant, and scalable systems that are cost-effective and meet business needs for data, services, and infrastructure.
• Performance Troubleshooting: Diagnose and resolve performance issues, including slow queries, resource contention, and bottlenecks across distributed storage engines and services.
• Cluster Scaling and Data Growth: Plan and implement strategies for scaling clusters to accommodate increasing data volume while optimizing performance and cost-efficiency.
• Documentation and Incident Response: Develop and maintain runbooks and SOPs; lead blameless incident response with post-incident analysis to drive continuous improvement.
• Big Data System Design: Architect and implement robust, scalable, and extensible big data systems that support core business and products, ensuring seamless data flow and system integration.
• On-Call Rotation: Participate in on-call rotations for production incidents, with availability to troubleshoot and resolve problems outside regular hours as needed.
• Incident Ownership and Analysis: Own incidents during on-call hours, coordinate escalations, and conduct thorough post-incident analyses to identify root causes and preventive measures.

Minimum Qualifications

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• Experience writing code in Java, Scala, Go, Python, or similar; strong scripting skills (e.g., Bash) for automation.
• Understanding of algorithms, data structures, complexity analysis, and software design for building scalable systems.
• Basic SQL (MySQL, PostgreSQL, or similar): ability to write queries, perform joins, use aggregates, and optimize basic SQL queries.
• Systems and Infrastructure: Knowledge of Linux/Unix, familiarity with system internals, networking, and resource management.
• Hands-on experience with observability tools such as Prometheus, Grafana, and OpenTSDB; familiarity with CI/CD pipelines and tools (e.g., Jenkins, GitLab CI).

Preferred Qualifications

• Experience with distributed processing frameworks like Apache Spark and Apache Flink for large-scale data processing and stream processing.
• Familiarity with Apache Kafka and Apache Hive integrations in data pipelines and stream processing.
• HiveSQL knowledge: writing, optimizing, and debugging queries on large datasets stored in Hadoop-based systems (Hive, HDFS, etc.).
• HiveSQL with Kafka Streams or Kafka Connect integration for real-time processing.
• Experience running production-grade services at scale; understanding of cloud-native technologies, networking, and storage management for high availability.
• Experience developing tools and APIs to reduce manual intervention and improve automation.
• Expertise in designing, analyzing, and troubleshooting large-scale systems (experience with Hadoop, Spark, Hive, Presto, Kafka, Flink or equivalents is a strong plus).

TikTok is the leading destination for short-form mobile video. U.S. Data Security (USDS) is a subsidiary of TikTok in the U.S. This division focuses on data protection policies and content assurance protocols to keep U.S. users safe. Our teams span across Trust & Safety, Security & Privacy, Engineering, User & Product Ops, Corporate Functions and more.

Data Security Statement This role requires the ability to work with systems designed to protect sensitive data and information and is subject to screening.

Inspiring creativity is at TikTok's core. Our mission is to inspire creativity and bring joy. We value curiosity, humility, and impact, and we strive to foster an inclusive, diverse environment where great people can do great things.

Acknowledgment of Country TikTok acknowledges the Traditional Custodians of country and pays respect to elders past and present.