Description
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.