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Our client is looking for a technical and strategic AI and Data Engineer to take ownership of AI and data engineering practices. You’ll play a central role in shaping modern data platforms, building production-grade AI solutions, and embedding best practices in data and AI engineering.
Key Responsibilities:
* Lead the design and delivery of scalable data architectures and pipelines to meet analytics and AI needs.
* Develop and maintain AI and data products aligned to business outcomes.
* Champion automation-first engineering practices across ingestion, transformation, and deployment.
* Design and deploy generative and predictive AI solutions using Azure and open-source frameworks.
* Implement modern DataOps and MLOps practices, including CI/CD pipelines and monitoring.
* Establish and maintain reusable enterprise data models and semantic layers for self-service analytics.
* Mentor and develop a high-performing engineering team.
* Collaborate with stakeholders to embed insight and AI in product delivery and business decision-making.
About You:
* Deep expertise in data engineering, data pipelines, and semantic models.
* Hands-on experience building data platforms on Microsoft Azure (Data Factory, Synapse, Databricks, Purview).
* Skilled in deploying machine learning models and generative AI applications in production.
* Strong programming skills in Python, SQL, YAML.
* Experience with CI/CD and infrastructure-as-code (e.g., Terraform/Bicep).
* Proven leadership in embedding modern engineering practices (DataOps, MLOps) within teams.
* Comfortable working in Agile development and structured deployment environments.
* Desirable experience with Azure OpenAI, LangChain, and graph/vector databases.
What’s on offer:
* Opportunity to lead the engineering backbone of a data-driven transformation.
* Work with forward-thinking teams in a culture of innovation and continuous learning.
* Flexible working, collaborative culture, and pathways for growth.
Apply here for more information and a full job spec.
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