TP-Link
Sr. Big Data Engineer - Data Infrastructure (Mandarin Bilingual Required)
TP-Link, Irvine, California, United States, 92713
About Us
TP‑Link Systems Inc. is a global provider of reliable networking devices and smart home products, consistently ranked as the world’s top provider of Wi‑Fi devices. With a commitment to excellence, TP‑Link serves customers in over 170 countries and continues to grow its global footprint. We believe technology changes the world for the better!
Key Responsibilities
Design and build scalable data pipelines: Develop and maintain high‑performance and large‑scale data ingestion and transformation, including ETL/ELT processes, data de‑identification, and security management.
Data orchestration and automation: Develop and manage automated data workflows using tools like Apache Airflow to schedule pipelines, manage dependencies, and ensure reliable, timely data processing and availability.
AWS integration and cloud expertise: Build data pipelines integrated with AWS cloud‑native storage and compute services, leveraging scalable cloud infrastructure for data processing.
Monitoring and data quality: Implement comprehensive monitoring, logging, and alerting to ensure high availability, fault tolerance and data quality through self‑healing strategies and robust data validation processes.
Technology innovation: Stay current with emerging big data technologies and industry trends, recommending and implementing new tools and approaches to continuously improve data infrastructure.
Technical leadership: Provide technical leadership for data infrastructure teams, guide architecture decisions and system design best practices. Mentor junior engineers through code reviews and knowledge sharing, lead complex projects from concept to production, and foster a culture of operational excellence.
Bilingual Mandarin Required
Requirements Required Qualifications
5+ years in data engineering, software engineering, or data infrastructure with proven experience building and operating large‑scale data pipelines and distributed systems in production, including terabyte‑scale big data environments.
Strong Python skills for building data pipelines and processing jobs, with ability to write clean, maintainable and efficient code. Experience with Git version control and collaborative development workflows is required.
Deep knowledge of distributed systems and parallel processing concepts. Proficient in debugging and performance tuning large‑scale data systems, understanding of data partitioning, sharding, consistency, and fault tolerance in distributed data processing.
Strong proficiency with big data processing frameworks such as Apache Spark and other relevant batch processing technologies.
Strong understanding of relational database concepts and data warehouse principles.
Hands‑on experience with data workflow orchestration tools like Apache Airflow or AWS Step Functions for scheduling, coordinating, and monitoring complex data pipelines.
Excellent problem‑solving skills with strong attention to detail and ability to work effectively in collaborative team environments.
Preferred Qualifications
Master’s degree in Computer Science or related field.
Exposure to AI patterns, knowledge base systems, and expert systems; experience with real‑time streaming processing frameworks such as Apache Kafka, Apache Flink, Apache Beam, or pub/sub systems.
Familiarity with NoSQL, NewSQL, key‑value, columnar, graph, document, and time‑series databases; experience designing and optimizing schemas for analytics use cases in modern data warehouses (Redshift, BigQuery, Databricks, Snowflake).
Additional programming languages such as Java or Scala.
Experience with AWS cloud platforms, infrastructure as code (CDK, Terraform) and container orchestration (Docker, Kubernetes) for automated environment setup and scaling.
Benefits Salary Range: $150,000 – $200,000
Free snacks and drinks, and provided lunch on Fridays
Fully paid medical, dental, and vision insurance (partial coverage for dependents)
Contributions to 401(k) funds
Bi‑annual reviews and annual pay increases
Health and wellness benefits, including free gym membership
Quarterly team‑building events
Equal Opportunity At TP‑Link Systems Inc., we are continually searching for ambitious individuals who are passionate about their work. We believe that diversity fuels innovation, collaboration, and drives our entrepreneurial spirit. As a global company, we highly value diverse perspectives and are committed to cultivating an environment where all voices are heard, respected, and valued. We are dedicated to providing equal employment opportunities to all employees and applicants, and we prohibit discrimination and harassment of any kind based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Beyond compliance, we strive to create a supportive and growth‑oriented workplace for everyone.
Please note, we do not accept third‑party agency inquiries and are not offering visa sponsorships at this time.
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Key Responsibilities
Design and build scalable data pipelines: Develop and maintain high‑performance and large‑scale data ingestion and transformation, including ETL/ELT processes, data de‑identification, and security management.
Data orchestration and automation: Develop and manage automated data workflows using tools like Apache Airflow to schedule pipelines, manage dependencies, and ensure reliable, timely data processing and availability.
AWS integration and cloud expertise: Build data pipelines integrated with AWS cloud‑native storage and compute services, leveraging scalable cloud infrastructure for data processing.
Monitoring and data quality: Implement comprehensive monitoring, logging, and alerting to ensure high availability, fault tolerance and data quality through self‑healing strategies and robust data validation processes.
Technology innovation: Stay current with emerging big data technologies and industry trends, recommending and implementing new tools and approaches to continuously improve data infrastructure.
Technical leadership: Provide technical leadership for data infrastructure teams, guide architecture decisions and system design best practices. Mentor junior engineers through code reviews and knowledge sharing, lead complex projects from concept to production, and foster a culture of operational excellence.
Bilingual Mandarin Required
Requirements Required Qualifications
5+ years in data engineering, software engineering, or data infrastructure with proven experience building and operating large‑scale data pipelines and distributed systems in production, including terabyte‑scale big data environments.
Strong Python skills for building data pipelines and processing jobs, with ability to write clean, maintainable and efficient code. Experience with Git version control and collaborative development workflows is required.
Deep knowledge of distributed systems and parallel processing concepts. Proficient in debugging and performance tuning large‑scale data systems, understanding of data partitioning, sharding, consistency, and fault tolerance in distributed data processing.
Strong proficiency with big data processing frameworks such as Apache Spark and other relevant batch processing technologies.
Strong understanding of relational database concepts and data warehouse principles.
Hands‑on experience with data workflow orchestration tools like Apache Airflow or AWS Step Functions for scheduling, coordinating, and monitoring complex data pipelines.
Excellent problem‑solving skills with strong attention to detail and ability to work effectively in collaborative team environments.
Preferred Qualifications
Master’s degree in Computer Science or related field.
Exposure to AI patterns, knowledge base systems, and expert systems; experience with real‑time streaming processing frameworks such as Apache Kafka, Apache Flink, Apache Beam, or pub/sub systems.
Familiarity with NoSQL, NewSQL, key‑value, columnar, graph, document, and time‑series databases; experience designing and optimizing schemas for analytics use cases in modern data warehouses (Redshift, BigQuery, Databricks, Snowflake).
Additional programming languages such as Java or Scala.
Experience with AWS cloud platforms, infrastructure as code (CDK, Terraform) and container orchestration (Docker, Kubernetes) for automated environment setup and scaling.
Benefits Salary Range: $150,000 – $200,000
Free snacks and drinks, and provided lunch on Fridays
Fully paid medical, dental, and vision insurance (partial coverage for dependents)
Contributions to 401(k) funds
Bi‑annual reviews and annual pay increases
Health and wellness benefits, including free gym membership
Quarterly team‑building events
Equal Opportunity At TP‑Link Systems Inc., we are continually searching for ambitious individuals who are passionate about their work. We believe that diversity fuels innovation, collaboration, and drives our entrepreneurial spirit. As a global company, we highly value diverse perspectives and are committed to cultivating an environment where all voices are heard, respected, and valued. We are dedicated to providing equal employment opportunities to all employees and applicants, and we prohibit discrimination and harassment of any kind based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Beyond compliance, we strive to create a supportive and growth‑oriented workplace for everyone.
Please note, we do not accept third‑party agency inquiries and are not offering visa sponsorships at this time.
#J-18808-Ljbffr