Data Engineer

Who are we?

• Skai (formerly Kenshoo) is a leading omnichannel marketing platform that uniquely connects data and performance media for informed decisions, high efficiencies, and optimal returns. Its partners include Google, Meta, Amazon Ads, TikTok, Snapchat, Walmart Connect, Instacart, Roundel, Criteo, CitrusAd, Pinterest, Microsoft, LinkedIn, Apple Search Ads, and more.
• We’re 700 employees strong and growing every day! ~$7 billion in ad spending is managed on the SkaiTM platform every year, driving hundreds of billions in commerce decisions and sales transactions.
• Established in 2006, we are a thriving organization with a unique startup culture, an incredible track record of success, and an amazing future in sight!
• We are hybrid for the long term, with a great home/office work mix, passionate and diverse team members, and a vibrant company culture.

What will you do:

As part of the Data Services team, you will be responsible for developing and managing complex data pipelines, real-time replications, and providing a robust, easy-to-use infrastructure for varied stakeholders. The role includes utilizing cloud-native tools, invoking POCs, architecture design, software development, and of course, providing roster support during non-working hours for critical systems.

You'll enjoy taking advantage of the cutting-edge technologies and "the right tool for the job" Skai has embraced over the years:

• Infra & cloud-native solutions: AWS
• Software development: Microservices with CI/CD, Container mgmt. on Kuberenetes
• DBs for varied needs: Snowflake, SingleStore, MySQL, Keyspaces, Elastic Cache
• E2E Monitor : DataDog
• And much more, from Kafka streaming to advanced queueing, image wrapping, proactive monitoring, infra as code etc.

What do you need:

• 5+ years of hands-on experience in developing with Python/Java.
• Demonstrated self-learning skills with the ability to independently explore and navigate new territories.
• Strong team player with excellent communication skills.
• Familiarity with microservices architecture, CI/CD pipelines, databases, Docker, Kubernetes and Kafka.
• Experience with cloud-native solutions (preferably AWS) using services such as S3, Glue, Lambda functions, etc.
• Support production issues (24/7).