At Slack, we are dedicated to revolutionizing the way people find and interact with information. Our mission is to build cutting-edge search technologies that deliver relevant and personalized results to our users. We are looking for a talented and passionate Search Infrastructure Data Engineer to join our team and help us achieve this goal! About the Team: The Core Infrastructure organization at Slack is responsible for designing, developing, and maintaining the information retrieval infrastructure that supports our Search, ML, and many other product experiences. This stack is at the heart of what makes Slack such a compelling store of company knowledge, allowing our customers to find and discover messages, channels, people, files, and other business units within their workspaces. We are also heavily invested in generative AI, helping build products that leverage the full wealth of knowledge in our company. Job Description: As a Search Infrastructure Data Engineer, you will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our search systems. You will work closely with internal teams and software developers to ensure that our search algorithms are efficient, scalable, and deliver high-quality results. This role helps power the entire Slack search indexing pipeline and is responsible for building highly scalable pipelines at petabyte scale to ensure all Slack users can search on and find their data. Key Responsibilities: Design and develop scalable and resilient information retrieval infrastructure to power search and other products. Build and integrate scalable backend systems, platforms, and tools that power our data warehouse and help our partners implement, deploy, and analyze data assets. Develop and maintain ETL processes to ensure data quality and consistency. Optimize data storage and retrieval to support real-time search queries and recommendations. Monitor and troubleshoot data pipelines in production. Participate in on-call rotation. Work with the Search Infrastructure teams to maintain and improve various data pipelines. Mentor other engineers and deeply review code. Improve engineering standards, tooling, and processes. Qualifications: Experience with big data technologies such as Spark, Map Reduce, Hadoop, Airflow, Hive, and Kafka. Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field. 6+ years of relevant technical experience, including significant experience in data engineering, with a focus on search. Experience with search technologies such as Elasticsearch, Solr, or Lucene. Proficiency in programming languages such as Python, Java, or Scala. Solid understanding of SQL and NoSQL databases. Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker, Kubernetes). Excellent problem-solving skills and attention to detail. Strong communication and collaboration skills. Preferred Qualifications: Familiarity with data visualization tools and techniques like Grafana, Logstash, or Splunk. Experience with vector-based retrieval systems like Vespa, Milvus, or Solr. #J-18808-Ljbffr Salesforce, Inc.
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