Big Data Developer

A tech company that has developed one of the largest job search marketplaces in America. The company has millions of customers and is growing very rapidly, operating as both a B2B and B2C company since its customers include both employers and job seekers. This dual focus presents a greater challenge and demands constant innovation.

About two years ago, the company went public and now has over 1,200 employees worldwide, spread across England, the United States, and, of course, here in Israel. In Israel, the development center has over 100 employees, with significant recruitment expected in 2023 as new tech teams are established.

The company's offices are located in Tel Aviv (near a train station) and operate in a hybrid work model.

The company still has a startup atmosphere, and one of its significant values is organizational culture and employee well-being.

Role description: The teams are interdisciplinary, including DS, DE, and BE. The role involves developing infrastructure for a product based on ML, working on the core of the product. This includes developing data pipelines and handling a lot of data, working at very high scales. The code is written in Python and Scala.

Key focuses:

• Build infrastructure to empower fellow engineers and data scientists to build together best-in-class machine learning based products
• Working in a high-volume production environment that gets bigger and bigger
• Mastering scalability and enterprise-grade production services implementation
• Sense of ownership - leading design for new products and initiatives as well as integrating with currently implemented best-practices
• Working with a number of modern technologies including Spark, Delta Lake, Elasticsearch, Kafka, DynamoDB, K8s, and more

Requirements:

• 5 years of coding experience with one of the following: Python, Scala.
• End-to-end experience - owning features from an idea stage, through design, architecture, coding, integration, and deployment stages
• Experience with one or more of these technologies Spark, Flink, MapReduce, Airflow, Kafka, Key/Value Stores like DynamoDB, SQL DB's
• Dealing with data on high volume, high availability production systems
• Fluent with SQL