

Numentica
Data Search Specialist
โญ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Search Specialist, a remote position for GC and US citizens, with a contract length of unspecified duration. Pay rate is competitive. Requires 5-10 years of experience, strong AWS knowledge, and hands-on skills in search systems and data governance.
๐ - Country
United States
๐ฑ - Currency
$ USD
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๐ฐ - Day rate
Unknown
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๐๏ธ - Date
July 18, 2026
๐ - Duration
Unknown
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๐๏ธ - Location
Remote
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๐ - Contract
Unknown
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๐ - Security
Unknown
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๐ - Location detailed
United States
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๐ง - Skills detailed
#S3 (Amazon Simple Storage Service) #Data Design #Data Pipeline #Data Engineering #AI (Artificial Intelligence) #Indexing #RDS (Amazon Relational Database Service) #AWS (Amazon Web Services) #Monitoring #Redshift #Base #SharePoint #Data Ingestion #Metadata #Data Quality #Classification #ML (Machine Learning) #OpenSearch #Athena
Role description
Role is for GC and US Citizens ONLY
The Data / Search Specialist makes the customer's knowledge usable by generative AI systems. On an embedded enablement pod, the specialist builds the connectors, knowledge bases, and retrieval layers that ground AI applications in approved enterprise content, while enforcing data classification and access boundaries and transferring these practices to customer staff. The role is hands-on and supports the architect and application engineers throughout delivery.
Key Responsibilities
โข Build and configure connectors and ingestion pipelines bringing approved enterprise content into knowledge bases, including SharePoint Online, Exchange/Outlook, OneDrive, and Teams.
โข Design and maintain knowledge base structures using Amazon Bedrock Knowledge Bases and Amazon OpenSearch, including chunking, metadata, and indexing strategies.
โข Integrate structured data sources such as Amazon Athena, Redshift, RDS, and S3 for retrieval and analysis.
โข Generate and manage embeddings and configure vector stores for retrieval.
โข Build a retrieval-evaluation framework and iteratively improve relevance, accuracy, and grounding/citation quality.
โข Implement document-level and user-level access enforcement so retrieval respects data classification, PHI/PII boundaries, and least-privilege principles.
โข Collaborate with the architect and engineers to align data design with the overall solution and evaluation goals, and transfer practices to customer staff.
โข Document data flows, indexing decisions, retrieval configurations, and connector feasibility for handover and reuse.
Required Qualifications
โข Hands-on experience with search, retrieval, or knowledge-base systems and the data pipelines that feed them.
โข Working knowledge of embeddings, vector stores, and RAG retrieval patterns.
โข Experience with data ingestion, connectors, indexing, and content preparation, ideally including Microsoft 365 sources.
โข Strong understanding of data permissions, document-level / user-level access control, data classification, and governance (including PHI/PII).
โข Familiarity with AWS data and AI services (e.g., Amazon Bedrock Knowledge Bases, OpenSearch, Athena/Redshift/RDS/S3) and core AWS fundamentals.
โข Strong problem-solving skills, attention to data quality, and ability to transfer practices to customer staff.
Preferred Qualifications
โข Experience with Amazon OpenSearch, Kendra, Amazon Q Business, or comparable enterprise search platforms.
โข Background in data engineering or information retrieval.
โข Experience building formal retrieval-evaluation methods and quality monitoring.
โข Exposure to regulated or public-sector environments.
โข AWS certification in data analytics or machine learning.
Location & Travel
โข This is a US-only position; candidates must be authorized to work in and based in the United States.
โข The role is primarily remote but may require travel up to 10% during the engagement for on-site workshops and customer sessions.
Experience Level
5 to 10 years of experience with at least 2 years of relevant technical stack experience.
Should understand AWS fundamentals in addition to the AI/data stack.
Role is for GC and US Citizens ONLY
The Data / Search Specialist makes the customer's knowledge usable by generative AI systems. On an embedded enablement pod, the specialist builds the connectors, knowledge bases, and retrieval layers that ground AI applications in approved enterprise content, while enforcing data classification and access boundaries and transferring these practices to customer staff. The role is hands-on and supports the architect and application engineers throughout delivery.
Key Responsibilities
โข Build and configure connectors and ingestion pipelines bringing approved enterprise content into knowledge bases, including SharePoint Online, Exchange/Outlook, OneDrive, and Teams.
โข Design and maintain knowledge base structures using Amazon Bedrock Knowledge Bases and Amazon OpenSearch, including chunking, metadata, and indexing strategies.
โข Integrate structured data sources such as Amazon Athena, Redshift, RDS, and S3 for retrieval and analysis.
โข Generate and manage embeddings and configure vector stores for retrieval.
โข Build a retrieval-evaluation framework and iteratively improve relevance, accuracy, and grounding/citation quality.
โข Implement document-level and user-level access enforcement so retrieval respects data classification, PHI/PII boundaries, and least-privilege principles.
โข Collaborate with the architect and engineers to align data design with the overall solution and evaluation goals, and transfer practices to customer staff.
โข Document data flows, indexing decisions, retrieval configurations, and connector feasibility for handover and reuse.
Required Qualifications
โข Hands-on experience with search, retrieval, or knowledge-base systems and the data pipelines that feed them.
โข Working knowledge of embeddings, vector stores, and RAG retrieval patterns.
โข Experience with data ingestion, connectors, indexing, and content preparation, ideally including Microsoft 365 sources.
โข Strong understanding of data permissions, document-level / user-level access control, data classification, and governance (including PHI/PII).
โข Familiarity with AWS data and AI services (e.g., Amazon Bedrock Knowledge Bases, OpenSearch, Athena/Redshift/RDS/S3) and core AWS fundamentals.
โข Strong problem-solving skills, attention to data quality, and ability to transfer practices to customer staff.
Preferred Qualifications
โข Experience with Amazon OpenSearch, Kendra, Amazon Q Business, or comparable enterprise search platforms.
โข Background in data engineering or information retrieval.
โข Experience building formal retrieval-evaluation methods and quality monitoring.
โข Exposure to regulated or public-sector environments.
โข AWS certification in data analytics or machine learning.
Location & Travel
โข This is a US-only position; candidates must be authorized to work in and based in the United States.
โข The role is primarily remote but may require travel up to 10% during the engagement for on-site workshops and customer sessions.
Experience Level
5 to 10 years of experience with at least 2 years of relevant technical stack experience.
Should understand AWS fundamentals in addition to the AI/data stack.





