Data Platform Engineer

at  Riskified

ABOUT US

Riskified empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world’s biggest brands and publicly traded companies selling online rely on Riskified for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, Riskified’s AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. Riskified is proud to work with incredible companies in virtually all industries including Wayfair, Acer, Gucci, Lorna Jane, GoPro, and many more.
We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day.

QUALIFICATIONS

• 4 years of experience as a Data Engineer
• Experience working with NoSQL & SQL databases
• Development experience with Spark or similar frameworks
• Experience with data lakes on HDFS or cloud storage (S3 or similar) - Advantage
• Experience with Python/Scala/Java - Advantage
• Experience working with K8S/docker etc - Advantage
• Experience in AWS cloud - Advantage

LIFE AT RISKIFIED

We are a fast-growing and dynamic tech company with 750+ team members globally. We value collaboration and innovative thinking. We’re looking for bright, driven, and passionate people to grow with us.
Our Tel-Aviv team is currently working in a hybrid of remote and in-office work. We have recently moved to our new space in Tel Aviv - check it out here!

Some of our Tel Aviv Benefits & Perks:

• Equity for all employees, Keren Hishtalmut, pension
• Private medical insurance, extra time off for parents and caregivers
• Commuter and parking benefits
• Team events, fully-stocked kitchen,lunch stipend, happy hours, yoga, pilates, functional training, basketball, soccer
• Wide-ranging opportunities to volunteer and make an impact
• Commitment to your professional development with global onboarding, skills-based courses, full access to Udemy, lunch & learns
• Awesome Riskified gifts and swag!

ABOUT THE ROLE

Big data analysis is at the core of our technology. Riskified’s broad spectrum of departments - from data science to performance analytics, to customer support and finance - all depend on fast and easy access to high-volume data. Our growth heavily depends on a system that can quickly and efficiently process data at scale.
Our revolutionary approach for Data Science, a key component in our success, relies heavily on our Big Data team to digest, process and serve data produced by billions of events per day.
Our key data pipelines include:
Streaming events in near real-time from multiple high-scale production services into our data lake. Processing data for our complex model training flow. Data pipelines supporting complex fraud detection patterns, potentially preventing fraud on a scale of millions of dollars per day (!).
Our Technological Stack includes: Scala/Spark, Databricks, Data Hub, Elasticsearch, Airflow, Snowflake, AWS, Kafka, Kubernetes, and more.
As a Data Platform Engineer, you will solve complex problems that require a varied and multi-disciplinary skill set. You’ll be required to understand the bigger picture, design system architecture, build highly complex data flows, and manage multiple, multi-faceted projects at once.

WHAT YOU’LL BE DOING

• Be a significant part of our data platform engineering - help our fraud detection engine make sub-second decisions, support our model training pipeline that ingests terabytes of data and provides near real-time BI and analytics to our customers
• Architect highly scalable data solutions for diversified and complex data flows using Apache Spark
• Build and develop high-performance, near real-time ETL processes incorporating Apache Kafka
• Improve our scheduler workflow engine operation