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Tech Stack
Tools & technologiesApacheAWSAzureDistributed SystemsElasticSearchJavaLinuxMS SQL ServerPythonSparkSQL
About the role
Key responsibilities & impact- 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
What you’ll need- 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.
Benefits
Comp & perks- Competitive compensation
- Health and Wellness programs
- Income Protection
- Paid Leave
- Retirement
ATS Keywords
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Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Apache SolrAWS OpenSearchSparkFlumeJavaPythonSQLindexingschema designperformance optimization
Soft Skills
analytical skillstroubleshooting skillsproblem-solving skillswritten communicationverbal communicationcollaborationattention to detailaccountability
Certifications
Bachelor's degree in Computer SciencePublic Trust Clearance