Search Engineer

Role Overview

• Maintain, support, and enhance enterprise search applications and indexing pipelines running on Solr, Spark, Flume, AWS OpenSearch, and Linux-based infrastructure.
• Perform operations and maintenance activities including patching, vulnerability management, system administration, monitoring, configuration management, and routine platform support.
• Troubleshoot and resolve indexing failures, data issues, query syntax problems, relevance issues, and search performance degradation.
• Monitor indexing jobs and platform health to ensure indexing SLAs and search/retrieval SLAs are consistently met.
• Fine-tune search configurations, analyzers, synonyms, ranking logic, and index structures to optimize search relevance, indexing throughput, and retrieval performance.
• Perform scheduled maintenance activities including weekly, monthly, and biannual data purges, index cleanup, retention-related tasks, and storage optimization.
• Support quarterly bulk indexing operations, including large-scale reloads, synonym refreshes, name normalization, and post-load validation.
• Work with source data stored in Microsoft SQL Server to investigate ingestion issues, validate upstream data quality, analyze indexing results, and review operational or search-related metrics captured after indexing.
• Use SQL to query source and operational data, investigate discrepancies, support troubleshooting, and validate indexing outcomes and SLA-related metrics.
• Use Azure Log Analytics and related monitoring tools to analyze logs, investigate failures, identify operational trends, and support root cause analysis for indexing, search, and data-processing issues.
• Maintain awareness of Java-based source-to-target data comparison and validation tools, review their findings regularly, and address data quality, synchronization, and accuracy issues between source systems and indexed search platforms.
• Investigate and resolve data ingestion, transformation, indexing, and retrieval issues across upstream and downstream systems.
• Build and improve automation, scripts, and support tooling that increases reliability, reduce operational overhead, and improve observability.
• Support modernization of legacy search capabilities toward AWS OpenSearch, semantic search, vector search, hybrid retrieval, and RAG-enabled solutions.
• Document procedures, runbooks, support processes, recurring maintenance activities, and operational findings, and collaborate with cross-functional teams to improve search quality and system stability.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field, or equivalent practical experience.
• 5+ years of experience in software engineering, enterprise search, search platform support, information retrieval, or large-scale data systems.
• Hands-on experience supporting and enhancing enterprise search platforms such as Apache Solr, OpenSearch, Elasticsearch, Lucene, or similar technologies.
• Experience working in Linux production environments, including troubleshooting, configuration updates, and routine system support.
• Strong experience with indexing, schema design, mappings, analyzers, query processing, search relevance tuning, and performance optimization.
• Experience supporting batch or large-scale data ingestion and processing pipelines using Spark and related technologies.
• Strong programming skills in Java and/or Python.
• Working knowledge of Microsoft SQL Server, including the ability to query source data, validate data flows, investigate discrepancies, and analyze indexing or operational metrics.
• Experience using log monitoring and observability tools to investigate failures and support operational troubleshooting; exposure to Azure Log Analytics strongly preferred.
• Experience troubleshooting distributed systems, indexing pipelines, data synchronization issues, and production search clusters.
• Experience supporting SLA-driven operational environments with accountability for service restoration, recurring maintenance, and issue resolution.
• Ability to understand and work with validation, comparison, and support tools used to verify data accuracy between source and target systems.
• Strong analytical, troubleshooting, and problem-solving skills.
• Strong written and verbal communication skills, including the ability to work across engineering, operations, and stakeholder teams.
• Work in US eastern time zone, and available to travel to Washington, DC area once a year.
• Ability to clear Public Trust Clearance.

Tech Stack

• Apache
• AWS
• Azure
• Distributed Systems
• ElasticSearch
• Java
• Linux
• MS SQL Server
• Python
• Spark
• SQL

Benefits

• Competitive compensation
• Health and Wellness programs
• Income Protection
• Paid Leave
• Retirement