Senior Data Context Engineer

POSITION:  Senior Data Context Engineer

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