Manager – AI Integration & Agentic Analytics Engineering

We are seeking an experienced Manager – AI Integration & Agentic Analytics Engineering to lead the development of intelligent enterprise data products, AI-powered reporting solutions, and modern integrations across our business platforms.

This individual will lead a team responsible for connecting enterprise source systems into our cloud data platform while championing the adoption of AI Agents to automate business processes, improve engineering efficiency, and deliver next-generation analytical capabilities.

Responsibilities

Leadership

• Lead and develop a high-performing team of analytics engineers, data engineers and AI developers.
• Build a culture focused on innovation, engineering excellence and continuous improvement.
• Coach engineers in modern software engineering, AI-assisted development and best practices.
• Drive technical strategy and delivery across multiple concurrent initiatives.
• Collaborate with Product Managers, Architecture, Security, Finance and Business stakeholders.

AI & Agentic Development

• Champion the adoption of enterprise AI technologies including:
• AI Agents
• Multi-agent workflows
• LLM orchestration
• Retrieval Augmented Generation (RAG)
• MCP (Model Context Protocol)
• Autonomous reporting
• Intelligent workflow automation
• AI-assisted software engineering
• Prompt engineering
• Agent evaluation frameworks
• Human-in-the-loop AI systems
• Identify opportunities where AI can automate manual reporting, business processes and operational decision making.
• Develop reusable AI capabilities that accelerate engineering productivity and improve customer outcomes.

Enterprise Integration

• Lead integrations across enterprise systems including financial, operational and commercial platforms such as:
• ERP systems
• Financial platforms
• CRM platforms
• Contract management systems
• Operational applications
• Internal APIs
• Third-party SaaS platforms
• Event-driven architectures
• Streaming data platforms
• Design reliable and scalable ingestion frameworks supporting both batch and real-time processing.

Data Engineering

• Drive engineering excellence across:
• Modern ETL / ELT
• Data pipelines
• Lakehouse architectures
• Data quality
• Metadata management
• Data governance
• Data observability
• Data lineage
• Performance optimisation
• CI/CD
• Infrastructure as Code
• Champion reusable engineering frameworks and platform standardization.

Financial & Enterprise Reporting

• Lead delivery of enterprise reporting supporting Finance and executive stakeholders.
• Develop scalable semantic models supporting:
• Financial reporting
• Operational reporting
• Executive dashboards
• KPI scorecards
• Regulatory reporting
• Forecasting
• Planning
• Variance analysis
• Ensure reporting is trusted, performant and capable of supporting AI-powered natural language querying.

Data Modelling

• Design enterprise-grade data models including:
• Kimball dimensional modelling
• Star schemas
• Snowflake schemas
• Data Vault concepts
• Semantic modelling
• Slowly Changing Dimensions
• Master Data Management
• Reference data
• Metrics modelling
• Partner with business stakeholders to ensure consistent enterprise definitions.

Platform & Technology

• Drive adoption of modern cloud technologies including:
• Databricks
• Delta Lake
• Unity Catalog
• Azure Data Factory
• Azure Data Lake Storage
• Power BI
• Azure AI
• Azure OpenAI
• Python
• SQL
• Spark
• PySpark
• REST APIs
• Git
• Azure DevOps
• Terraform
• Docker
• Kubernetes

Operational Excellence

• Develop monitoring and AI-powered observability across enterprise data products.
• Improve:
• Platform reliability
• Data quality
• Incident response
• Engineering productivity
• Operational intelligence
• Release automation
• Performance monitoring
• Use AI to proactively detect anomalies before they impact customers.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems or related discipline.
• Significant experience leading technical engineering teams.
• Experience delivering enterprise data platforms.
• Strong experience with cloud data engineering.
• Experience integrating enterprise source systems.
• Strong SQL and Python skills.
• Experience building scalable reporting solutions.
• Experience with dimensional modelling.
• Experience delivering financial reporting solutions.
• Experience working with APIs and enterprise integrations.
• Excellent stakeholder management and communication skills.

What You’ll Deliver

• AI-powered enterprise reporting capabilities.
• Intelligent agentic workflows that automate manual business processes.
• Modern integrations across enterprise source systems.
• Scalable financial and operational data products.
• Trusted semantic models supporting self-service analytics.
• High-quality engineering standards across the analytics platform.
• Increased engineering productivity through AI-assisted software development.
• Enterprise AI capabilities that transform how business users interact with data.