Data Engineer Big Data Pipelines

The ideal candidate has hands-on data processing experience. Candidate must be familiar with current distributed computing data technologies on commodity servers and have experience with 24×7 production needs.

Requirements

• Strong SQL skills on large-scale databases, knowledge of any of the following RDBMS such as MySQL, Postgres, Redshift, Hive or others.

• Experience with Linux or Unix based systems – including Bourne shell, cron and other Unix utilities.

• Strong software development skills, including experience with Java.

• Degree in Computer Science or a related field

Desired Technology Experience

• Experience with at least one of Ruby/Python, Bourne Shell or other scripting languages.

• Experience with Hadoop/Map Reduce and/or EMR, including experience in developing Map Reduce Jobs in Java or developing Hive UDF.

• ETL experience maintaining multiple data systems.

• Experience with Ooozie or other Hadoop workflow solutions and experience developing complex data processing pipelines, including experience developing regressions tests and deployment strategies for such environments.

• Experience with data reporting solutions – either developed in house or with 3rd party solutions.

• Working experience developing and supporting 24×7 production data services and pipelines on Linux systems – including experience being on-call supporting such services. Experience with AWS preferred.

Challenges we are tackling

• Reliably processing billions of events per day with no data loss 24×7 on commodity hardware.

• Processing events in near real-time

• Building for the fragility of cloud and distributed services

• Complex processing of large amounts of data in an efficient manner.

• Reporting, distribution of data, data analysis, data visualization and machine learning algorithms.

• Low latency data stores for use in bidding or algo optimization.