Careers at Bigabid

Big Data Engineer

Bigabid is an innovative technology company led by data scientists and engineers  devoted to mobile app growth.  Our proprietary ad platforms powered by machine learning are a culmination of that devotion. We deliver valuable results and insights for a fast growing clientele of major app developers using elite programmatic user acquisition and retargeting technologies.

Our ever evolving, state-of-the-art machine learning technology analyzes tens of TB of raw data per day to produce millions of ad recommendations in real-time.

 We are looking for an experienced Big Data Engineer to join our Data Engineering team. 

The perfect candidate will work independently as a team member in an Agile fast-paced development environment and will take a major part in designing and implementing complex high scale systems using a large variety of Big Data technologies.

Responsibilities:

  • Develop and automate large scale, high-performance data processing systems (batch and/or streaming) to drive Bigabid’s Audience Management Platform growth and unique abilities.
  • Build scalable Spark data pipelines leveraging Airflow.
  • Design our data models for optimal storage and retrieval and to meet critical product and business requirements.
  • Contribute to shared Data Engineering tools & standards to improve the velocity and quality of output for the Data teams in the company (DS, DA, DE)
  • Improve data quality by using & improving internal tools to automatically detect issues
  • End to end experience - owning feature from an idea stage, through design, architecture, coding, integration, and deployment stages

Requirements:

  • +5 years experience as a Data Engineer/Big Data Engineer/Backend Engineer – Must
  • Advanced coding experience in Python and Spark – Must
  • Great SQL - Adventage
  • Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions
  • Experience designing and deploying high-performance systems with reliable monitoring and logging practices
Please fill out the form below to submit your interest.

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