Platform Analytics Developer

What you will do

• Under the guidance of the Assistant Director you design, deliver and maintain impactful data and analytical solutions, applying best practices and creative problem-solving to meet evolving user needs.
• More specifically you will:
• Support the design of scalable, resilient, and maintainable architectures of Fabric platform
• Own the end-to-end lifecycle of data products, from ingestion and transformation to semantic modeling and consumption across Corporate Administration and Operations
• Define and enforce platform standards, governance, and best practices
• Contribute to and help shape the platform roadmap and strategy
• Evaluate, test, and implement new tools, capabilities, and platform features
• Provide operational support for delivery of integrated, high-impact enterprise solutions
• Integrate DataOps/DevOps practices(CI/CD, automated testing, deployment pipelines) into core infrastructure
• Design and build production-grade data pipelines for batch and real-time use cases
• Develop reusable, scalable data assets aligned to a data-as-a-product approach
• Establish and maintain semantic layers and data modeling standards
• Enable and upskill team members through coaching, standard, and training initiatives
• Leverage AI tools (e.g. Power Automate, Data Activator) to accelerate development and automate workflows.
• What you need to succeed
• You are a collaborative and adaptable professional who thrives in a fast-paced environment. You communicate effectively with both technical and non-technical audiences, contribute to or leads discussions, and approach complexity and change with a solution-oriented mindset. .
• You bring:
• Strong experience in analytics engineering, data platform development or related roles.
• Proven ability to design and deliver end-to-end, scalable data and analytics solutions
• Expertise in Fabric architecture and modern data platforms (e.g. Lakehouse Environments)
• Advanced skills in data and semantic modeling, distributed processing (e.g. Spark) and pipeline orchestration