Data Platform Engineer

PocketMath is currently increasing its data science team to drive the shift on how mobile impressions are sold today through the development of effective programmatic buying algorithms while building out consumer analytics to better understand user engagement.

We offer you exciting technical challenges in a highly skilled environment. By being part of the data science team, working with data scientist and software engineers, your good development skills will contribute to create powerful, fast and robust system that handle billions events per day.

You will help the team to develop and integrate the products and strategy to constantly improve our real-time product decision.

What you will do

• Integrate RTB data onto our big data infrastructure
• Design solutions that can support strong scalability requirements and deliver performance and reliability with massive (billions events per hour)
• Develop new data processes to support new data integration
• Implement, test, and maintain best logical and physical modeling practices on various data platforms to cleanly integrate into existing enterprise data models; executing data model components to achieve efficient storage utilization and best query performance
• Tune reports, loaders, table design, indexes, and stored procedures to deliver required performance
• Define and execute plan for measuring and maintaining data integrity throughout the workflow

What you need to have:

• Experience with real-time and distributed systems, data streaming systems
• Good programming skills, in preference with: Java, Scala, C#, C , Python.
• Strong knowledge about data structures, concurrency and distributed systems.
• Good programming practices.
• Optimistic and self-motivated.
• Critical and analytical mind.
• Love to learn and take up exciting technical challenges.

Experienced in the following is a BIG plus:

• Has deployed apps on Amazon Web Services.
• Has used Messaging systems like: RabbitMQ, ZeroMQ.
• Has worked with Streaming platforms like: Amazon Kinesis, Apache Kafka.
• Experience in Complex Event Processing systems like: Apache Storm, Esper, SQLStream, FeedZai Pulse.
• Experience with the Hadoop Stack (HDFS, MapReduce, HBase, Hive, Pig, Spark, Shark).
• Experience with machine learning algorithms for classification, clustering, regression and recommendation.
• Experience with scientific and analytics platform : MatLab, R, SAS
• Has a track record of successful implementation of system handling large volume of data.
• Has Knowledge of Real-Time Bidding and Digital Advertising environment