Riskified Published: December 23, 2018
Job Type
Category
Level of education
Undergraduate
Level of Hebrew
Medium
Location of job
Tel Aviv/ Ramat Gan
How many relevant years experience do you require for the role:
More than 3 years

Description

Big data analysis is at the core of our technology, and we need a system that can quickly and efficiently process data at scale. Our Data Team manages the infrastructure that houses our sophisticated risk engine and directly supports Riskified’s growth. This team plays a crucial role in scaling and expanding our operations, and we’re looking for a multi-disciplinary Senior Data Engineer to build and manage the backbone of Riskified’s risk engine.

As a Senior Data Engineer, you will solve complex problems that require a varied and multi-disciplinary skill set. You understand the bigger picture and have experience designing system architecture and highly complex data flows, but you also pay close attention to detail and can manage multiple, multi-faceted projects at once.

Responsibilities
- Be a significant part of our data operation - Help our fraud detection engine make sub-second decisions, support our model training pipeline, ingesting terabytes of data and provide near real-time BI and analytics to our customers
- Architect highly scalable data solutions for diversified and complex data flows
- Build and Develop high-performance, near real-time ETL processes
- Administer Riskified's data infrastructures including: Postgresql, Redshift, Elasticsearch, DynamoDB, MongoDB, redis, Amazon Kinesis and more
- Perform benchmarks for new technologies

Requirements

- BSc Computer Science/Data Management or Mamram (IDF)
- At least 5 years of hands-on experience with large production scale NoSQL databases, for example, Mongodb/Elasticsearch/Cassandra etc - must
- At least 3 years of hands-on experience with relational databases - for example, Postgresql/MySql/Oracle/Oracle/ SQL/Mysql etc - must
- Hands-on software engineering experience in Scala/Ruby or similar - must
- Experience in Data Warehousing - strong advantage
- Experience in additional big data technologies - for example, Spark/Kafka/Hadoop etc - strong advantage
- Experience in AWS cloud - strong advantage
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