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IT Data Office Full Stack Engineer
Parent Job Family: Data and AI | Job Family: Data Governance
Role Purpose
The IT Data Office defines enterprise data governance, standards, policy, and enabling technology. This role designs, builds, and operates secure, scalable data products for analytics, machine learning, RAG, and agentic AI. The engineer delivers governed pipelines, knowledge graphs, vector databases, APIs, MCP endpoints, and end-to-end RAG platforms, owning design, engineering, deployment, monitoring, optimization, documentation, automation, and Agile delivery.
Key Responsibilities
- Identify source data, attributes, lineage, and relationships.
- Ingest data through APIs into Snowflake using dbt and Fivetran.
- Transform and integrate data into reusable products with embedded privacy, classification, access controls, roles, and privileges.
- Create and optimize APIs and MCP endpoints for SLM, LLM, and agentic AI use.
- Register products in Collibra and Immuta.
- Monitor and tune Snowflake, dbt, Fivetran, MuleSoft, and Anthropic integrations.
- Build ontologies, controlled vocabularies, and AWS Neptune knowledge graphs for RAG and autonomous agents.
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Education, Qualifications, and Experience
Essential:
- Bachelor’s degree in Computer Science, Data Management, or another STEM discipline.
- 5–10 years’ data management, business analysis, or data engineering experience with strong problem-solving skills.
- Proven delivery of data products, APIs, SLM/LLM solutions, knowledge-graph, or vector-database RAG architectures, and MCP endpoints.
Desirable:
- Master’s degree in Computer Science or Data Management, or equivalent experience.
- Experience managing ontologies and controlled vocabularies for complex knowledge graphs.
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Skills and Capabilities
Technical:
- Snowflake, dbt, SQL, Fivetran, Python, React, APIs, MuleSoft, and data security.
- AWS, infrastructure as code, Bedrock, Nova, Neptune, RDF, SPARQL, vector databases, SLM fine-tuning, RAG, and agentic AI.
- Anthropic MCP, Microsoft Copilot Studio, Agent Builder, DevOps, and performance tuning.
Professional:
- Customer focus, initiative, ownership, clear documentation, and dependable delivery.
- Cross-cultural collaboration and ability to influence senior leaders on plans, risks, and technical approaches.
- Working knowledge of Collibra and Immuta.
Key Relationships
- Collaborate with product managers, data and system owners, data scientists, ontologists, architects, analysts, security, and platform teams, and partners.
- Support prioritized IT transformation and enterprise data-product delivery.
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Jessica, London
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