Search Engineering Manager



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As a Search Engineering Manager, you will oversee and manage Search Engineers in the development, maintenance, testing and optimizing the search engine for a company’s platform. You are able to construct scalable and reliable workflows that efficiently process big datasets. While the Search Engineering Manager is involved with the technical aspects of the Search Engineering role, they also must complete common managerial duties and ensure organizational goals are being met.


  • Developing and operating search software, including indexing, query parsing and algorithms.
  • Designing and deploying high-performance RESTful web services.
  • Scaling search server clusters to accommodate increasing traffic by performance tuning.
  • Improving search relevance using text matching algorithms and NLP techniques.
  • Implementing and deploying machine learning models to production systems.
  • Find, import, and make searchable public data that will be used to optimize the search process.
  • Build and utilize metrics for analyzing relevance and ranking.
  • Develop systems that integrate with real-time data services and sources.
  • Design search engine monitoring tools, as well as scalable backend services and tools.
  • Craft libraries, schedule data pipelines and manage access data assets.
  • Implement major components for data pipelines and analytics platforms.
  • Improve the reliability, efficiency, scalability and latency of existing services and processes.
  • Collaborate with data analysts, developers and others in a cross-functional team to resolve problems.


  • 4+ years in software development and programming.
  • 3+ years of working with ETL, big data, datasets and NoSQL.
  • 3+ years of using search engine platforms such as ElasticSearch, Lucene, Solr or Endeca.
  • Experience implementing search engine platforms, including shards, builds of indexes and refined searches across structured, unstructured and semi-structured datasets.
  • Experience with resource planning and architectural design.
  • Experience with automated processes and techniques for bulk indexing of large-scale datasets.
  • Experience implementing microservices and Java applications.
  • Experience doing distributed queuing with technologies like Kafka.
  • Familiarity with version control like Git and AWS.
  • Strong understanding of programming languages such as Java, SQL, C++, Python or Scala.
  • Proficiency with data processing algorithms.
  • Excellent project management, organizational, analytical, problem-solving and communication skills.
  • B.S or M.S. degree in computer science, software or data engineering, information systems or other related fields.

These Would Also Be Nice

  • Experience with Jenkins, Maven, MapReduce, Spark, Hadoop, Hive or TensorFlow.
  • Experience with Python machine learning libraries and Linux environments.
  • Experience with Java JVM tuning and debugging.
  • Experience with Node.js, React.js and PHP frameworks.
  • Familiarity with mobile technologies such as Android, iOS and React Native.

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