TikTok
Overview
SRE, Data Management and Applications - USDS The Data Engineering team in Data Platform USDS is focused on ensuring the stability, reliability, scalability and risk management of TikTok's U.S. data processing ecosystem. We maintain and operate both batch and streaming pipelines for multiple vertical businesses such as TikTok and TikTok Shop while simultaneously adhering to strict data compliance standards. We collaborate with a host of internal teams to better enable user experiences by delivering high quality at scale. Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed services and infrastructures. As a site reliability engineer in the data platform area, you will manage the services and infrastructures in one of the largest data platforms in the world that directly supports the TikTok app. You'll need to ensure the data, services and infrastructures are reliable, fault-tolerant, efficiently scalable and cost-effective. In order to enhance collaboration and cross-functional partnerships, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager / department.
Responsibilities
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 both cost-effective and efficient, ensuring data, services, and infrastructure meet business needs.
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 effectively to accommodate increasing data volume while optimizing performance and cost-efficiency.
Documentation and Incident Response : Develop and maintain clear runbooks, Standard Operating Procedures (SOPs), and lead sustainable, blameless incident response practices with post-incident analysis to drive continuous improvement.
Big Data System Design : Architect and implement robust, scalable, and extensible big data systems that support the core business and products, ensuring seamless data flow and system integration.
On-Call Rotation : Participate in on-call rotations for production incidents, ensuring critical issues are addressed swiftly, with availability to troubleshoot and resolve problems outside of regular business hours as needed.
Incident Ownership and Analysis : Take ownership of incidents during on-call hours, coordinate escalations as necessary, and conduct thorough post-incident analyses to identify root causes and implement preventive measures.
Minimum Qualifications
Bachelor's degree in Computer Science, a related technical field involving software or systems engineering, or equivalent practical experience.
Experience writing code in Java, Scala, Go, Python, or a similar language. Strong scripting skills (e.g., Bash and Shell) for automation tasks.
Experience with algorithms, data structures, complexity analysis, and software design : Solid understanding of how to build scalable and efficient systems.
Basic SQL (MySQL, PostgreSQL, or similar) : Strong understanding of traditional relational databases like MySQL or PostgreSQL. Ability to write queries, perform joins, use aggregate functions, and optimize basic SQL queries.
Systems and Infrastructure : Knowledge of Linux / Unix systems, as most infrastructure is based on Linux. Familiarity with system internals, networking, and resource management (memory, CPU, storage).
Hands-on experience with observability tools such as Prometheus, Grafana, & OpenTSDB : For monitoring, logging, and real-time performance tracking.
CI / CD Tools : Familiarity with Continuous Integration / Continuous Deployment pipelines and tools (e.g., Jenkins, GitLab CI, Aegis, Bits).
Preferred Qualifications
Strong troubleshooting and debugging skills to work in a fast paced on-call environment.
Familiarity with containerized deployments such as Docker / Kubernetes.
Experience running production-grade services at scale : Understanding of cloud-native technologies, networking, and storage management to support high-availability and large-scale environments.
Experience developing tools and APIs : To reduce human intervention in systems administration and improve automation and operational efficiency.
Expertise in designing, analyzing, and troubleshooting large-scale systems : Experience with Hadoop, Spark, Hive, Presto, Kafka, Flink, or comparable solutions is a strong plus.
As a condition of employment, all successful candidates must be able to establish authorization to work in the United States. For this position, the Company does not provide sponsorship for any immigration-related benefits.
USDS is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws.
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SRE, Data Management and Applications - USDS The Data Engineering team in Data Platform USDS is focused on ensuring the stability, reliability, scalability and risk management of TikTok's U.S. data processing ecosystem. We maintain and operate both batch and streaming pipelines for multiple vertical businesses such as TikTok and TikTok Shop while simultaneously adhering to strict data compliance standards. We collaborate with a host of internal teams to better enable user experiences by delivering high quality at scale. Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed services and infrastructures. As a site reliability engineer in the data platform area, you will manage the services and infrastructures in one of the largest data platforms in the world that directly supports the TikTok app. You'll need to ensure the data, services and infrastructures are reliable, fault-tolerant, efficiently scalable and cost-effective. In order to enhance collaboration and cross-functional partnerships, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager / department.
Responsibilities
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 both cost-effective and efficient, ensuring data, services, and infrastructure meet business needs.
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 effectively to accommodate increasing data volume while optimizing performance and cost-efficiency.
Documentation and Incident Response : Develop and maintain clear runbooks, Standard Operating Procedures (SOPs), and lead sustainable, blameless incident response practices with post-incident analysis to drive continuous improvement.
Big Data System Design : Architect and implement robust, scalable, and extensible big data systems that support the core business and products, ensuring seamless data flow and system integration.
On-Call Rotation : Participate in on-call rotations for production incidents, ensuring critical issues are addressed swiftly, with availability to troubleshoot and resolve problems outside of regular business hours as needed.
Incident Ownership and Analysis : Take ownership of incidents during on-call hours, coordinate escalations as necessary, and conduct thorough post-incident analyses to identify root causes and implement preventive measures.
Minimum Qualifications
Bachelor's degree in Computer Science, a related technical field involving software or systems engineering, or equivalent practical experience.
Experience writing code in Java, Scala, Go, Python, or a similar language. Strong scripting skills (e.g., Bash and Shell) for automation tasks.
Experience with algorithms, data structures, complexity analysis, and software design : Solid understanding of how to build scalable and efficient systems.
Basic SQL (MySQL, PostgreSQL, or similar) : Strong understanding of traditional relational databases like MySQL or PostgreSQL. Ability to write queries, perform joins, use aggregate functions, and optimize basic SQL queries.
Systems and Infrastructure : Knowledge of Linux / Unix systems, as most infrastructure is based on Linux. Familiarity with system internals, networking, and resource management (memory, CPU, storage).
Hands-on experience with observability tools such as Prometheus, Grafana, & OpenTSDB : For monitoring, logging, and real-time performance tracking.
CI / CD Tools : Familiarity with Continuous Integration / Continuous Deployment pipelines and tools (e.g., Jenkins, GitLab CI, Aegis, Bits).
Preferred Qualifications
Strong troubleshooting and debugging skills to work in a fast paced on-call environment.
Familiarity with containerized deployments such as Docker / Kubernetes.
Experience running production-grade services at scale : Understanding of cloud-native technologies, networking, and storage management to support high-availability and large-scale environments.
Experience developing tools and APIs : To reduce human intervention in systems administration and improve automation and operational efficiency.
Expertise in designing, analyzing, and troubleshooting large-scale systems : Experience with Hadoop, Spark, Hive, Presto, Kafka, Flink, or comparable solutions is a strong plus.
As a condition of employment, all successful candidates must be able to establish authorization to work in the United States. For this position, the Company does not provide sponsorship for any immigration-related benefits.
USDS is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws.
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