Senior Data Context Engineer

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Employee Full-Time Indirect Jupiter, FL, US

LOCATION: Jupiter, FL.

STATUS: Salary Exempt

Position Summary

We are seeking a highly skilled Senior Data Context Engineer to design, build, and manage the enterprise data foundation that powers Artificial Intelligence (AI), analytics, and cloud-based business applications. This role is responsible for ensuring enterprise data is accurate, secure, governed, and contextually enriched to support AI solutions, business intelligence, and data-driven decision-making.

The Data Context Engineer Lead will collaborate with business stakeholders, application owners, cloud engineers, data engineers, and AI teams to integrate data from enterprise SaaS applications, AWS services, and on-premises systems into a trusted, scalable, and secure data ecosystem.

Key Responsibilities

• Design and maintain enterprise data context models that improve AI, analytics, and business reporting.
• Integrate data from enterprise SaaS applications into AWS data platforms.
• Design, develop, and maintain scalable data ingestion, transformation, and integration pipelines using AWS services.
• Manage enterprise data stored in Amazon S3 as the organization's centralized data lake.
• Develop and optimize datasets for Amazon QuickSight dashboards, analytics, and executive reporting.
• Support AI initiatives by preparing structured and unstructured data for Amazon Bedrock, Retrieval-Augmented Generation (RAG), and Large Language Models (LLMs).
• Design and maintain vector databases and semantic search capabilities to improve AI response accuracy.
• Build metadata, lineage, business glossaries, taxonomies, and enterprise data catalogs.
• Implement data quality controls, validation processes, and continuous monitoring to ensure data integrity.
• Define and maintain data lineage, ownership, and governance policies across enterprise systems.
• Collaborate with application owners to onboard new SaaS applications into the enterprise data platform.
• Develop and maintain APIs and integration services for secure data exchange between cloud and on-premises systems.
• Optimize cloud storage strategies, lifecycle policies, and data organization within Amazon S3.
• Partner with Data Scientists, Data Engineers, Digital Strategy, Security, Infrastructure, and Business Intelligence teams to deliver trusted enterprise data.
• Support the implementation of enterprise AI solutions using Amazon Bedrock and other AWS AI services.
• Ensure compliance with enterprise security policies and regulatory frameworks, including ISO 27001, CMMC, GDPR, and applicable data governance standards.
• Create technical documentation, architecture diagrams, data dictionaries, and operational procedures.
• Other duties as assigned.

Required Qualifications

• Bachelor's degree in Computer Science , Information Systems, Data Engineering, Cloud Computing, or a related field.
• 3+ years of experience in data engineering, cloud data platforms, business intelligence, or enterprise data management.
• Experience working with AWS cloud services.
• Strong SQL and Python programming skills.
• Experience integrating enterprise SaaS applications using APIs and cloud-native integration services.
• Strong understanding of relational databases, data lakes, and ETL/ELT methodologies.
• Experience with metadata management, data governance, and data quality practices.
• Knowledge of REST APIs, JSON, and data integration technologies.
• Excellent analytical, communication, and problem-solving skills.

Preferred AWS Experience

• Experience with several of the following is highly desirable:
• Atlan Data Catalog, Amazon S3, Amazon QuickSight , Amazon Bedrock, AWS Glue, AWS Lambda, Amazon Redshift, Amazon Athena, AWS Lake Formation, AWS IAM, AWS Step Functions, Amazon API Gateway, AWS AppFlow , Amazon EventBridge , Amazon OpenSearch Service, AWS Secrets Manager, AWS CloudWatch, and other related AWS services.

Preferred Qualifications

• Experience implementing AI and Generative AI solutions.
• Knowledge of Retrieval-Augmented Generation (RAG).
• Experience with vector databases and semantic search.
• Experience with LangChain , LlamaIndex , or similar AI frameworks.
• Experience with enterprise data catalog solutions such as Microsoft Purview, Collibra, or Alation.
• Familiarity with data warehouse architectures .
• Experience supporting enterprise reporting and business intelligence platforms.
• Understanding of cybersecurity and enterprise compliance requirements.

Equal Opportunity Employer Veterans/Disabled

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