Data Engineer

new york, NY 10012

Industry: Data Engineer Job Number: 4391
 
Who we’ re looking for

Data plays an integral role in our product, and software engineers on our data engineering team build the pipelines that power reporting and analytics for our e-commerce promotions platform. The infrastructure and applications that you' ll build on the data engineering team will have broad and critical reach in powering real-time auction decisions, becoming multipliers on our revenues, and forecasting supply and demand for our customers.

Responsibilities
  • Ship high-quality, well-tested, secure, and maintainable code
  • Design, develop, and maintain data pipelines and back-end services for real-time decisioning, reporting, optimization, data collection, and related functions
  • Manage automated unit and integration test suites
  • Work collaboratively and communicate effectively with a small, motivated team of engineers and product managers
  • Experiment with and recommend new technologies that simplify or improve the stack
  • Participate in an on-call rotation and work occasional off-hours

Qualifications
  • BS/MS in Computer Science or a related technical field
  • Seeking candidates with 4+ years of experience in:
  • Architecting, building, and maintaining end-to-end, high-throughput data systems and their supporting services
  • Designing data systems that are secure, testable, and modular, particularly in Python, as well as their support infrastructure (shell scripts, job schedulers, message queues, etc.)
  • Designing efficient data structures and database schemas
  • Working with distributed systems architecture
  • Incorporating data processing and workflow management tools into pipeline design (AWS EMR, Airflow, Kafka, etc.)
  • Using profiling tools, debugging logs, performance metrics, and other data sources to make code- and application-level improvements
  • Developing for continuous integration and automated deployments
  • Utilizing a variety of data stores, including data warehouses (ideally Redshift), RDBMSes (ideally MySQL), in-memory caches (ideally Aerospike and Redis), and searchable document DBs (ideally Elasticseach)
  • Wrangling large-scale data sets

 

Rachel Newell
Technical Recruiter

A California native who packed her things and moved to NYC on a whim in 2011. By blind luck, she fell into the world of recruiting in March of 2012. A fun fact people probably wouldn't guess about her, most likely because she has a tendency to trip over her own two feet, is that she played Division 1 college soccer at Arizona State. It was there that she also found her love for travel when she studied abroad in Rome. If Rachel isn’t matchmaking people with new jobs, you can find her globetrotting around exploring new corners of the world.

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