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Position Overview

The Senior Power BI Developer is responsible for designing, developing, and supporting scalable Business Intelligence solutions using Microsoft Power BI and associated Microsoft data technologies.

This role combines technical expertise, business analysis, stakeholder engagement, solution architecture, and mentoring responsibilities. The successful candidate will work directly with clients and internal teams to transform complex business requirements into actionable analytics and visually compelling dashboards.

The role requires a strong understanding of data modelling, DAX, Power Query, SQL, Azure data services, and modern BI development practices.

Key Responsibilities

Solution Design & Development

• Design, develop, and maintain Power BI dashboards, reports, scorecards, and analytical solutions.
• Build scalable semantic models using best-practice dimensional modelling techniques.
• Develop complex DAX measures, calculated columns, and KPIs.
• Create intuitive and visually compelling dashboards suitable for executive and operational users.
• Implement report security using Row-Level Security (RLS) and Power BI governance standards.
• Optimise dashboard performance and usability.

Data Integration & Data Modelling

• Design and develop data models to support reporting and analytical requirements.
• Connect and integrate data from various sources including:
  • SQL Server
  • Snowflake
  • Azure Data Lake
  • SharePoint
  • Excel
  • APIs
  • ERP and business systems
• Develop Power Query transformations and ETL processes.
• Ensure data quality, consistency, and integrity across reporting solutions.

Business Analysis & Stakeholder Engagement

• Conduct workshops and requirements gathering sessions with business stakeholders.
• Translate business requirements into technical specifications and solution designs.
• Assist clients in defining KPIs, metrics, and reporting standards.
• Present solutions and demonstrate dashboards to stakeholders and leadership teams.
• Provide advice on reporting strategy and analytics best practices.

Technical Leadership

• Lead the technical delivery of Power BI projects.
• Review and approve development work completed by junior developers.
• Establish development standards, coding standards, and governance practices.
• Mentor and support junior developers and analysts.
• Participate in solution architecture and design reviews.

Project Delivery & Support

• Contribute to project planning, effort estimation, and delivery governance.
• Conduct unit testing, system testing, and user acceptance testing support.
• Produce technical and functional documentation.
• Support production deployments and hypercare activities.
• Troubleshoot and resolve reporting and data issues.

Continuous Improvement

• Stay current with Microsoft Fabric, Power BI, Azure Data Services, and emerging analytics technologies.
• Identify opportunities for automation and process improvement.
• Contribute to reusable assets, templates, and internal accelerators.

Required Skills & Experience

Technical Skills

• 5+ years' experience developing enterprise solutions with Microsoft Power BI.
• Advanced DAX development skills.
• Strong Power Query (M Language) skills.
• Strong SQL development experience.
• Experience designing dimensional data models.
• Experience integrating data from multiple enterprise systems.
• Experience working with Power BI Service, Gateways, Deployment Pipelines, and Workspaces.
• Strong understanding of Power BI governance, security, and performance optimisation.
• Experience with Microsoft Fabric, Azure Synapse, Azure Data Factory, or similar cloud technologies.
• Familiarity with source control and DevOps practices.

Business & Consulting Skills

• Strong stakeholder engagement and communication skills.
• Ability to facilitate workshops and gather requirements.
• Strong analytical and problem-solving ability.
• Experience working directly with enterprise clients.
• Ability to explain technical concepts to non-technical audiences.

Desirable Skills

• Microsoft Fabric experience.
• Azure Data Engineering experience.
• Power Apps and Power Automate experience.
• Snowflake experience.
• Experience delivering solutions within mining, resources, manufacturing, utilities, or government sectors.
• Relevant Microsoft certifications.

Qualifications

• Bachelor's degree in Information Technology, Computer Science, Data Analytics, Engineering, or a related discipline.
• Microsoft Power BI Certification preferred.
• Microsoft Fabric or Azure certifications highly regarded.

Position Summary

The Senior Technical Lead is responsible for leading the technical delivery of enterprise applications, AI solutions, data platforms, and cloud-based systems. This is a hands-on role requiring active participation in solution design, software development, code reviews, troubleshooting, DevOps, and technical mentoring.

Unlike a traditional architecture role, this position is expected to remain close to the code, rapidly validate ideas through prototypes, solve complex engineering challenges, and guide delivery teams through implementation.

The successful candidate will combine strong leadership skills with deep technical expertise across software engineering, cloud platforms, AI technologies, integration patterns, and modern development practices.

Key Responsibilities

Technical Leadership

• Provide day-to-day technical leadership across delivery teams.
• Lead design and implementation of complex software solutions.
• Translate business requirements into practical, implementable technical solutions.
• Mentor developers and establish engineering best practices.
• Drive technical decision making and technology selection.

Hands-On Software Development

• Actively contribute to application development and solution delivery.
• Build proof-of-concepts and technical accelerators.
• Develop and review production-quality code.
• Assist teams with complex debugging, performance optimisation, and solution design.
• Contribute to architecture while remaining accountable for delivery outcomes.

AI & Intelligent Solutions

• Design and develop AI-powered solutions using modern AI frameworks.
• Deliver solutions incorporating:
  • Generative AI
  • RAG architectures
  • Agentic workflows
  • Semantic search
  • Intelligent automation
• Build and integrate AI services into enterprise business processes.

Cloud & DevOps

• Build and deploy cloud-native solutions on Azure and AWS.
• Implement CI/CD pipelines and DevOps practices.
• Support monitoring, logging, performance tuning, and operational readiness.
• Champion automation across development and deployment processes.

Delivery & Engineering Excellence

• Lead sprint planning and technical workstream delivery.
• Ensure solutions meet security, performance, scalability, and supportability requirements.
• Conduct code reviews and technical quality assessments.
• Support estimation, planning, and risk mitigation activities.

Stakeholder Engagement

• Collaborate directly with business stakeholders, project managers, product owners, and architects.
• Participate in technical workshops and solution discussions.
• Communicate technical concepts clearly to both technical and non-technical audiences.

Required Technical Skills

Software Engineering

• Strong software development experience using:
  • Python
  • Node.js
  • TypeScript / JavaScript
  • REST APIs
• Experience building scalable enterprise applications.

AI & Data Engineering

• Experience delivering GenAI solutions and AI-enabled applications.
• Knowledge of:
  • LLM platforms
  • RAG implementations
  • Vector databases
  • AI orchestration frameworks
  • Semantic search technologies

Cloud Platforms

• Azure and/or AWS experience.
• Containerisation and Docker.
• CI/CD pipelines and DevOps tooling.
• Monitoring and observability platforms.

Data & Integration

• API-led integration design.
• SQL and NoSQL databases.
• Data modelling and data platform concepts.
• Event-driven and distributed architectures.

Leadership Experience

• Experience leading technical teams of 5+ engineers.
• Proven ability to guide developers through technical delivery challenges.
• Strong mentoring and coaching capabilities.
• Ability to balance technical excellence with pragmatic delivery outcomes.

Key Deliverables

• Working software solutions
• Technical designs and implementation plans
• AI prototypes and production solutions
• Code reviews and engineering standards
• CI/CD and deployment frameworks
• Technical documentation
• Performance and optimisation improvements
• Knowledge transfer and mentoring outcomes

Position Summary

The Senior GenAI Engineer is responsible for designing, developing, deploying, and supporting enterprise-grade Generative AI solutions on AWS. This is a hands-on engineering role focused on building production-ready AI applications, agentic workflows, intelligent automation solutions, and scalable cloud-native platforms.

The successful candidate will work across software engineering, AI engineering, cloud infrastructure, and DevOps disciplines to deliver secure, robust, and maintainable solutions. They will actively contribute code, infrastructure, and deployment pipelines while providing technical leadership and mentoring to delivery teams.

This role is expected to spend the majority of its time building and deploying solutions rather than producing architecture artefacts.

Core Responsibilities

GenAI Solution Development

• Design and develop enterprise Generative AI applications.
• Build and deploy autonomous AI agents and multi-agent workflows.
• Develop Retrieval Augmented Generation (RAG) solutions using enterprise data sources.
• Integrate Large Language Models (LLMs) into business processes and applications.
• Build AI-powered assistants, copilots, and intelligent automation services.
• Implement AI guardrails, observability, evaluation, and monitoring capabilities.

Agent Framework Development

• Develop solutions using modern agentic frameworks including:
  • Strands Agents
  • LangGraph
  • Agent orchestration platforms
  • MCP integrations
• Build reusable agent components and workflow accelerators.
• Implement tool calling, planning, memory, and multi-agent collaboration patterns.

AWS Cloud Engineering

• Design and implement AI solutions using AWS-native services.
• Develop serverless architectures using:
  • AWS Lambda
  • API Gateway
  • Step Functions
  • SQS/SNS
  • EventBridge
• Deploy and manage workloads across AWS environments.
• Implement secure, scalable, and highly available cloud solutions.

Infrastructure & DevOps

• Build and maintain Infrastructure as Code using Terraform.
• Develop CI/CD pipelines for application and infrastructure deployments.
• Implement automated testing and deployment practices.
• Configure cloud monitoring, logging, alerting, and operational dashboards.
• Support platform reliability, performance tuning, and operational readiness.

Software Engineering

• Develop production-grade software solutions using Python.
• Build APIs, integrations, and backend services.
• Perform peer code reviews and quality assurance activities.
• Troubleshoot and resolve complex production issues.
• Contribute to engineering standards and best practices.

Required Experience

AWS

Strong experience with:

• AWS Lambda
• API Gateway
• Step Functions
• S3
• DynamoDB
• EventBridge
• ECR/ECS
• IAM
• CloudWatch
• Bedrock
• Secrets Manager
• VPC networking concepts

Infrastructure as Code

Experience with:

• Terraform
• GitOps practices
• Automated environment provisioning
• Multi-environment deployment strategies

Generative AI

Practical experience building:

• RAG applications
• AI agents
• Agent orchestration workflows
• Enterprise AI assistants
• Knowledge retrieval platforms
• LLM-based automation solutions

Development

Strong hands-on experience with:

• Python
• REST APIs
• JSON/OpenAPI
• Microservices architectures
• Asynchronous processing patterns
• Event-driven architectures

DevOps

Experience with:

• CI/CD pipelines
• GitHub Actions
• Containerisation
• Docker
• Monitoring and observability
• Secure software development practices

Nice to Have

• Amazon Bedrock
• Strands Agent Framework
• LangGraph
• Vector Databases
• OpenTelemetry
• Kafka
• Kubernetes
• MCP Server development
• AI evaluation frameworks
• Enterprise AI governance

What Success Looks Like

The successful candidate:

• Builds production AI solutions on AWS.
• Writes and reviews code daily.
• Designs and deploys infrastructure using Terraform.
• Leads technical delivery through hands-on contribution.
• Develops reusable GenAI capabilities and accelerators.
• Improves engineering standards across the team.
• Mentors developers while remaining actively involved in implementation.