Data & Analytics Platform Architect

About Nova Source

Nova Source Power Services is the world’s #1‑ranked solar operations and maintenance (O&M) provider and insight‑driven total asset optimization partner for renewables asset owners ready to fuel smart growth. With over 20 years of operating experience and a presence on five continents, Nova Source has the global reach and strategic capabilities to achieve our clients’ renewables goals around the world.

Nova Source’s comprehensive approach to total asset optimization in addition to O&M services includes value engineering, performance analysis, strategic supply chain management, and advanced monitoring systems. The company operates in key global markets managing over 40GW of solar power plants. Nova Source’s expertise extends beyond solar and includes battery energy storage systems (BESS), offering a complete suite of services for the evolving renewable energy landscape.

We are seeking a hands‑on Data & Analytics Platform Architect to serve as the technical authority for our enterprise data platform — designing, building, and continuously evolving the systems that power contractual, operational, analytical, and AI‑driven workloads across the organization. This role combines strategic architecture with deep engineering ownership: you will lead the evolution of our Azure and Databricks‑based data ecosystem, refine our multi‑layer data pipelines, implement data mesh principles across multiple repositories, and drive high levels of automation to ensure a reliable, scalable, and cost‑efficient platform.

You will also explore and integrate emerging technologies — including AI/LLM capabilities — to enhance the platform’s intelligence and business value. Strong collaboration, commitment to incremental delivery, and the ability to mentor technical teams are essential.

• Architect, build, and continuously improve the enterprise data platform, ensuring reliability, scalability, and maintainability across core business processes and analytics use cases.
• Own the full data platform lifecycle — from schema design and pipeline architecture to monitoring, performance tuning, and incident response.
• Establish and enforce data modeling standards, naming conventions, and governance frameworks across all environments.
• Implement policy enforcement points and access controls (data catalogs, encryption, RBAC) to ensure compliance, privacy, and data protection.

• Design, build, and evolve dimensional data models — including star schemas on Azure Databricks — optimized for analytics and reporting.
• Develop and refine medallion architecture (bronze‑silver‑gold layers) for efficient data ingestion, transformation, and consumption.
• Balance model simplicity, flexibility, and performance while minimizing redundancy across analytical datasets.

• Lead the design and evolution of the Databricks intelligent data platform, enabling scalable big data processing and laying the foundation for AI/ML capabilities.
• Architect and manage Azure‑based infrastructure including Azure SQL, Azure Data Factory, Azure Synapse Analytics, Data Lake, and related services.
• Apply data mesh principles across multiple data repositories to enable decentralized, domain‑oriented data ownership.

• Ensure ETL/ELT processes and pipeline tools (Azure Data Factory, Databricks/Spark) run efficiently to deliver timely, high‑quality data for analytics, BI, and AI/ML.
• Design and implement automation to significantly reduce recurring DBA and operational tasks, minimizing manual intervention.
• Develop monitoring, alerting, and self‑healing mechanisms to proactively maintain…