We've done alot of business with this client over the last few years, helping them through a very exciting growth phase. This is a self funded and profitable company so not your typical VC-backed startup. Our client delivers high quality products to global consumers through a continuous focus on data-driven decisions and creation of engaging content. After achieving profitability after only 7 months of operation, the company is in the process of scaling the initial engineering team into a robust development team ready to tackle any technical challenges for continued growth.
We are seeking a data-driven engineer with a firm handle on AWS data pipelines who is also capable of backend engineering on some special projects. The current data ingestion pipeline consists of Lambda, Kinesis, Firehose, Redshift, PySpark and Airflow. As the Backend/Data Engineer, you will be combining behavioral data, business systems data, transactional data and third party data into a real-time analytics pipeline that drives all of the critical business decisions we make. This role has a wider scope than the traditional Backend Developer or Data Engineer role so you will have an immediate impact on every aspect of a rapidly growing business. You will have decision making ability to suggest and improve on our current services and architecture to ensure we are consistently using the best solutions possible.
- 5+ Years in Engineering with at least 6 months of Data Engineering experience
- AWS Expertise with Redshift specifically, Lambda and Kinesis preferred
- Pyspark or Spark
- Data Pipelines
- Airflow experience is a plus
- Transparent and upbeat communication style