Data Engineer – Tel Aviv

Forter is looking for a talented data engineer with broad experience and a passion for building scalable and resilient systems, to join us in the challenge of combating online fraud. This engineer would be helping to catch sophisticated fraudsters in real-time, at large scale, for the biggest enterprises in the world.

We need our engineers to be independent, versatile, and enthusiastic to take on new problems across the vast tech stack with which we work. We don’t have dedicated “Production,” Ops, or QA teams, but rather everyone does a bit of everything, and therefore each individual has a big impact on Forter.

Stuff you’ll be doing:

• Developing and being responsible for distributed, high-throughput, large-scale production systems, handling billions of events per day.
• Supporting and conducting the flow for providing effective data points needed for real-time decisioning, from research to production.
• Crafting tools and practices to analyze complex datasets (e.g. imagine complex joins between multiple data sources with billions of records in each).
• Working with colleagues from various disciplines – Analysts, data scientists, researchers, and fellow engineers.
• Working with production clusters of various datastores and data processing engines, including Spark, Storm, ElasticSearch, Couchbase, Redis, MySQL, Redshift and Athena.
• Debugging complex problems across the whole stack
• Self-managing projects planning, milestones, designs, and estimations

Stuff you’ll need:

• Strong skills with several of the following: Python, Java, Kotlin, NodeJS
• Proven experience with designing and building large-scale production systems
• Deep knowledge of different data stores such as MySQL, Postgres, Elasticsearch, Couchbase, AeroSpike, MongoDB, Cassandra, DynamoDB, Redis, etc.
• Have been a “go-to” person in your previous teams/organizations
• Experience with AWS or other public clouds
• Professional proficiency in English

We’d love it if you have:

• Very strong understanding of how to explore and extract insights from data: SQL capabilities (RDS/Athena/Redshift), using Spark to process billions of data points, etc.
• Advanced experience in stream processing and data processing tools and best-practices