Data Engineer, E-Commerce

Responsibilities

• 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

Benefits

• This role may be eligible for additional discretionary bonuses/incentives
• This role may be eligible for restricted stock units
• Day one access to medical, dental, and vision insurance
• A 401(k) savings plan with company match
• Paid parental leave
• Short-term and long-term disability coverage
• Life insurance
• Wellbeing benefits
• 10 paid holidays per year
• 10 paid sick days per year
• 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)
• Glassdoor
• 3.2
• TikTok is a short-form video entertainment app and social network platform. It is a sub-organization of ByteDance.
• Los Angeles, California, USA
• https://www.tiktok.com
• Distribution of Different Job Fields Receiving Sponsorship
• Represents job field similar to this job
• Engineering and Development
• Product Management
• Management and Executive
• Sales
• Customer Service and Support
• Creatives and Design
• Legal and Compliance
• Accounting and Finance
• Arts and Entertainment
• Human Resources
• Education and Training

Qualifications

• 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

Required skills

• ClickHouse, Data Modeling, ETL, Flink, Flume, Hadoop, Hive, Kafka, MapReduce, Presto, SQL, Spark

Experience

• Mid level