Data Engineer, E-Commerce

Tiktok Inc
San Jose, CA, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Data Analysis Big Data Databases Data Infrastructure Data Integration Extract Transform Load (ETL) Data Systems R (Programming Language) Apache Hadoop Apache Hive SQL Databases Data Ingestion
+9 more
Apache Spark Build Management Apache Flume Information Technology Apache Flink Apache Kafka Data Management Presto Vertica

Job description

As a Data Engineer in the Data Platform E-Commerce team, you will have the opportunity to build, optimize and grow one of the largest data platforms in the world. You ll have the opportunity to gain hands-on experience on all kinds of systems in the data platform ecosystem. Your work will have a direct and huge impact on the company s core products as well as hundreds of millions of users., * 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. Minimum Qualifications

Requirements

eCommerce, eCommerce, Ecosystems, Analysis Skills, Big Data, Product Support, Best Practices, Computer Science, Data Analysis, Database Extract Transform and Load (ETL), * BS or MS degree in Computer Science or related technical field or equivalent practical experience;

  • Experience in the 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;
  • Experience with ETL(Extraction, Transformation & Loading) and architecting data systems;
  • Experience with schema design, data modeling and SQL queries;
  • Passionate and self-motivated about technologies in the Big Data area.

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