<div class="content-intro"><h3 class="ms-outlook-mobile-reference-message skipProofing">Experience Without Limits Come shape the future of brand experience.</h3> At Jack Morton, we design and build head-turning, smile-inducing, impact-driving brand experiences that redefine what experiential marketing can achieve. We help our clients unlock the full value of experiences by turning bold ideas into meaningful connections. That takes a team that's bold, curious, and acts as one. We build on each other's ideas, challenge conventions, and show up for one another every day. Here, you'll do your best work, grow quickly, and partner across clients, disciplines, and global teams to bring new ideas to life. This is a place where curiosity drives what’s next, boldness raises the bar, and every win is shared. Where ownership is expected, egos are left at the door, and the work reflects the passion and talent of the people behind it. Experience without limits—in your work, your growth, and your impact.</div>Freelance Data Engineer (Security) Jack IQ Programme  ·  Role details Job title | Data Engineer (Security) Reports to | Product Lead / Technology Executive Contract type  Freelance (to perm possible) Duration ASAP – April 27 Location / working pattern  - Remote Start date ASAP Purpose of the role Jack Morton is seeking a Data Engineer to help build out the data spine for an AI-enabled event intelligence platform. The role will focus on creating secure and scalable processes to connect operational systems, unstructured project documentation and data from third-party platforms into existing data warehousing infrastructure. The successful candidate will help transform fragmented agency knowledge into governed, searchable, AI-ready assets while ensuring adherence to privacy, retention, and client-specific data requirements.   Key responsibilities <ul> <li>Create a structured data layer to integrate and model structured data from API enabled sources such as CRM systems, Azure databases, event attendance systems, survey platforms, and financial warehouses.</li> <li>Create ingestion pipelines for the unstructured knowledge layer that includes Powerpoint presentations, Word documents and unstructured Excel spreadsheets.</li> <li>Build an AI-Ready document infrastructure that can classify documents, handle versioning, track provenance, and manage metadata, auditability and permissioning.</li> <li>Implement frameworks for strictest confidentiality and privacy protections, including access controls and security roles, consent tracking, data retention and data deletion management.</li> <li>Work with members of the Jack Morton team to clearly communicate limitations, timeline expectations, out-of-pocket cost expectations and repercussions to platform design.</li> <li>Participate in planning discussions on platform roadmap with Jack Morton team members.</li> </ul>   Data engineering requirements Pipeline design, ingestion, schema, data quality, orchestration, tooling. This role requires strong experience in the following: <ul> <li>Python</li> <li>SQL</li> <li>Data Modeling</li> <li>Data Warehousing (Snowflake experience is desirable)</li> <li>ETL or ELT development</li> <li>API Integrations</li> <li>Batch and event-driven pipelines.</li> </ul> The applicant should understand: <ul> <li>Metadata extraction</li> <li>OCR workflows</li> <li>Semantic indexing</li> <li>Vector databases</li> <li>Retrieval-Augmented Generation (RAG)</li> <li>Chunking strategies</li> <li>Document classification</li> <li>Embedding pipelines</li> </ul>   Security requirements Access control, tenant isolation, key management, pseudonymisation, audit and logging, compliance frameworks. Experience with the following is essential, with AI-specific experience being a bonus: <ul> <li>PII handling and understanding of GDPR implications</li> <li>Data pseudonymization</li> <li>Data lineage</li> <li>Retention policies</li> <li>Audit logging</li> <li>Data access controls</li> </ul> Platform and tooling Snowflake, AWS, Bedrock, integration patterns, languages, infrastructure as code. <ul> <li>Snowflake</li> <li>AWS Cognito</li> <li>AWS S3</li> <li>AWS Lamda</li> <li>AWS DynamoDB</li> </ul>   Experience required <ul> <li>Azure or Snowflake data warehousing</li> <li>Document ingestion and RAG experience</li> <li>Data governance and security</li> <li>Modern data modeling skills</li> <li>API integration</li> <li>Data pipelines for unstructured documentation</li> <li>Experience explaining technical infrastructure to non-technical teams</li> </ul>   Experience preferred   <ul> <li>LLM model building</li> <li>Understanding of event and experiential marketing</li> <li>Experience working with a project-based business</li> </ul>   First 90 days What success looks like by day 30, 60 and 90. Within the first 90 days the data engineer should be integrated into the platform team. They should have delivered a proposal for their plan for th…

Freelance Data Engineer (Security)

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