Sr. Search Engineer
Confirmed live in the last 24 hours
Slickdeals

201-500 employees

Community-driven platform for vetting and sharing deals
Company Overview
Slickdeals, a leading shopping site in the U.S., leverages the power of community and human intelligence to ensure consumers get the best deals, with its 12 million users vetting and voting for top products from renowned retailers. The company has saved its users a staggering $10 billion, demonstrating its significant competitive advantage in the market. Its culture of collaboration, coupled with technical tools like a free app, browser extensions, and a cashback rewards program, make it an engaging and rewarding place to work.
Consumer Goods
Data & Analytics

Company Stage

N/A

Total Funding

N/A

Founded

1999

Headquarters

San Mateo, California

Growth & Insights
Headcount

6 month growth

4%

1 year growth

-20%

2 year growth

-16%
Locations
San Mateo, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
MySQL
SQL
AWS
MongoDB
Google Cloud Platform
CategoriesNew
Data Engineering
Data Management
Data & Analytics
Requirements
  • 8+ years total professional experience as a software engineer
  • Substantial development and administration experience in search technology (Elasticsearch,Opensearch, Apache Solr, and/or Algolia)
  • Experience in performance tuning, query analysis, defining success criteria and metrics,designing ranking and relevance experiments and optimizing Elasticsearch
  • Knowledge of high availability and disaster recovery options for search
  • Exposure to a variety of data stores and search technologies (e.g. MySQL, RDS, MongoDB,DynamoDB, Redis, Open Search, Elasticsearch, Neo4j)
  • Familiarity with AWS, GCP and/or other cloud computing platforms
  • Prior experience with Python, SQL, and/or GraphQL
  • Understanding of best practices in database design, data architecture, and performancetuning
  • First-hand experience in building, scaling, and supporting large-scale data infrastructuresystems in production
  • Hands-on experience in building machine learning-based search and recommendationsystems
  • Experience with implementing ML-based search systems such as query classification,learning to rank or machine-learned ranking (MLR) search is a plus
Responsibilities
  • Working with data scientists and engineers to productionize cutting-edge data products viaload testing, metrics analysis, and offline and online experimentation, so they can scale tosupport millions of buyers around the world.
  • Designing and implementing features to improve the relevance of search andrecommendation experiences, including semantic search, query understanding, andpersonalization.
  • Building and maintaining data pipelines to power our information retrieval systems.
  • Tuning the ElasticSearch (or similar search technology) queries that power our search anddiscovery experiences.
  • Prioritizing and communicating to technical and non-technical audiences alike
  • Mentoring engineers and data scientists