Tech Lead Software Engineer for Data Platform

Team Introduction:

Our mission in experimentation and evaluation team is to build the next-gen A/B testing platform, that empowers the company to make data-driven decision for the products. The supported scenarios include recommendation, push, ads, search, mobile app, UI interaction and service upgrades etc. Our platform's capabilities cover the entire experiment life cycle, from experiment design, experiment creation, metrics calculation, statistical analysis to final evaluation and launch. In the process of rapid iteration, we provide reliable services for businesses to make bold hypotheses and cautious verification.

As a software engineer in experimentation and evaluation team, you will have the opportunity to build, optimize and grow one of the largest data platforms in the world. Your work will have a direct and huge impact on the company's core products as well as hundreds of millions of users.

What you'll do:

• Design and build data transformations efficiently and reliably for different purposes (e.g. reporting, growth analysis, multi-dimensional analysis)

• Design and implement reliable, scalable, robust and extensible big data systems that support core products and business

• Establish solid design and best engineering practice for engineers as well as non-technical people

•Prefer Mandarine and Chinese

• BS or MS degree in Computer Science or related technical field or equivalent practical experience

• Experience in big data technologies (Hadoop, M/R, Hive, Spark, Metastore, Presto, Flume, Kafka, ClickHouse, Flink etc.)

• Experience with performing data analysis, data ingestion and data integration

• Solid communication and collaboration skills Preferred Qualifications

• Working industry experience with Big Data systems and projects • Experience in building large scale distributed systems in a product environment

• Experience with ETL (Extraction, Transformation & Loading), architecting data systems, schema design, and data modeling

• Experience in data privacy.