{"schemaVersion":"jobsearcher.job.v1","id":"7dce207a82a580109f6145e0","url":"https://jobsearcher.com/jobs/7dce207a82a580109f6145e0","canonicalUrl":"https://jobsearcher.com/jobs/7dce207a82a580109f6145e0","title":"Data & Analytics Platform Architect","description":"About NovaSource\n\nNovaSource 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 5 continents, NovaSource has the global reach and strategic capabilities to achieve our clients’ renewables goals around the world.\n\nNovaSource’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. NovaSource’s expertise extends beyond solar and includes battery energy storage systems (BESS), offering a complete suite of services for the evolving renewable energy landscape.\n\nPosition Overview\n\nWe 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.\n\nKey Responsibilities\n\nEnterprise Data Platform Architecture & Engineering\n\nArchitect, build, and continuously improve the enterprise data platform, ensuring reliability, scalability, and maintainability across core business processes and analytics use cases.\nOwn the full data platform lifecycle — from schema design and pipeline architecture to monitoring, performance tuning, and incident response.\nEstablish and enforce data modeling standards, naming conventions, and governance frameworks across all environments.\nImplement policy enforcement points and access controls (data catalogs, encryption, RBAC) to ensure compliance, privacy, and data protection.\n\nAnalytical Data Modeling & Schema Design\n\nDesign, build, and evolve dimensional data models — including star schemas on Azure Databricks — optimized for analytics and reporting.\nDevelop and refine medallion architecture (bronze-silver-gold layers) for efficient data ingestion, transformation, and consumption.\nBalance model simplicity, flexibility, and performance while minimizing redundancy across analytical datasets.\n\nCloud & Big Data Architecture\n\nLead the design and evolution of the Databricks intelligent data platform, enabling scalable big data processing and laying the foundation for AI/ML capabilities.\nArchitect and manage Azure-based infrastructure including Azure SQL, Azure Data Factory, Azure Synapse Analytics, Data Lake, and related services.\nApply data mesh principles across multiple data repositories to enable decentralized, domain-oriented data ownership.\n\nPipeline Optimization & Automation\n\nEnsure 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.\nDesign and implement automation to significantly reduce recurring DBA and operational tasks, minimizing manual intervention.\nDevelop monitoring, alerting, and self-healing mechanisms to proactively maintain platform health and SLA adherence.\nIdentify and resolve bottlenecks, continuously tuning for performance and scalability.\n\nDomain-Specific Solutions\n\nDesign and implement algorithms supporting availability guarantees, contractual agreement calculations, regulatory reporting (e.g., GADS), and other domain-specific requirements.\nServe as Subject Matter Expert (SME) for performance engineering — profiling, tuning, and resolving issues across database and pipeline layers.\n\nAI & Agentic Capabilities Integration\n\nIncorporate AI and agentic capabilities as complementary components of the data platform.\nDesign and evolve secure LLM integration patterns using enterprise LLM gateways to centralize model access, routing, governance, and cost controls.\nLeverage frameworks like Model Context Protocol (MCP) to connect AI applications and agents with enterprise data sources in a secure, governed manner — enabling intelligent, agent-driven data workflows.\n\nDocumentation, Collaboration & Enablement\n\nPartner with business stakeholders, product teams, and engineering groups to translate requirements into scalable data solutions.\nCreate and maintain clear documentation for data architecture, integration processes, and platform best practices in collaboration with the Enterprise Architecture team.\nProvide technical leadership and mentorship within the technology team; establish best practices and participate in design reviews.\nCollaborate with third-party vendors and system integrators on data platform integrations and joint delivery initiatives.\n\nRequired Qualifications\nBachelor’s degree in Computer Science, Data Engineering, Data Science, or a related field.\n10+ years of experience designing and evolving large-scale data analytics platforms, with deep expertise in data integration (ETL/ELT), medallion-tier pipelines, cloud data services, and MLOps.\nDeep expertise in SQL — query optimization, schema design, indexing strategies, stored procedures, and performance tuning across platforms such as Microsoft SQL Server or Azure SQL.\nHands-on experience with Microsoft Azure data services (Azure SQL, Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, Blob Storage).\nProven experience designing and building on Databricks, including Delta Lake, Spark jobs, and cluster management.\nStrong familiarity with data lakehouse architecture and applying data mesh principles across enterprise environments.\nProven experience with: Azure Data Services (Synapse, Data Factory, Data Lake), Delta Lake, Azure Databricks\nSolid understanding of enterprise data governance, security (access controls, data privacy), and data quality best practices.\nDemonstrated success automating DBA and data operations tasks to significantly reduce manual workload.\nExperience working with contractual or regulatory reporting requirements in data-intensive industries (e.g., energy, utilities, or finance).\nStrong communication and interpersonal skills; ability to work effectively with both technical and non-technical stakeholders across multiple concurrent priorities.\n\nPreferred Qualifications\nExperience integrating AI/ML or LLM solutions into data platforms (e.g., Azure Cognitive Services, LLM gateways for multi-provider model integration, or context frameworks like MCP for AI-driven data products).\nExperience with energy sector data systems, including solar forecasting, GADS reporting, or availability guarantee frameworks.\nExperience with DevOps practices for data: CI/CD pipelines for database deployments, infrastructure-as-code (Terraform, Bicep, ARM templates).\nKnowledge of data security, encryption at rest/in transit, and RBAC in cloud environments.\nMicrosoft Certified: Azure Data Engineer Associate or Databricks Certified Data Engineer Professional.\nExperience partnering with third-party data vendors and managing vendor-delivered integrations.\nMaster’s degree in a relevant field.\n\nTechnical Skills Summary\n\nDatabases & SQL: SQL Server, Azure SQL, T-SQL, query optimization, indexing, stored procedures.\n\nCloud Platform: Azure Data Factory, Synapse Analytics, Data Lake, Blob Storage, Azure SQL.\n\nBig Data / AI: Azure Databricks, Apache Spark, Delta Lake, AI/ML pipeline foundations, LLM integration.\n\nArchitecture Patterns: Medallion architecture, data mesh, data warehousing, ETL/ELT, dimensional modeling on Azure Databricks.\n\nAutomation & DevOps: Pipeline automation, CI/CD for data, scripting (Python, PowerShell, or equivalent).\n\nGovernance & Security: Data catalogs, RBAC, encryption, data quality, compliance frameworks.\n\nMonitoring & Ops: Alerting, performance monitoring, incident mitigation, SLA management.\n\nWorking at NovaSource Power Services:\n\nWe value employee life outside of work and provide many ways to accommodate and support our staff in achieving their goals. You'll find a few ways we enact this below:\n\nExperience comes in many forms, many skills are transferable, and passion goes a long way. If the job description gets you pumped but your background isn’t exactly what we’ve described above, or if you strongly believe you bring qualifications beyond what we’ve outlined that would help you excel in this position, please consider applying.\n\nPotential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role.\n\nUS: Diversity Statement – Equal Employment Opportunity\n\nIt is NovaSource’s policy to provide equal employment opportunities to all applicants and employees. NovaSource disapproves of, and will not tolerate, unlawful discrimination against any applicant or employee because of race, color, national origin or ancestry, gender (including pregnancy, childbirth, or related medical conditions), gender identity, age, religion, disability, family care status, veteran status, marital status, sexual orientation, or any other basis protected by local, state or federal laws.","company":"Novasourcepowerservices","rawCompany":"novasourcepowerservices","city":"Chandler","state":"AZ","isRemote":false,"isActive":false,"createdAt":"2026-08-22T13:23:53.858Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data & Analytics Platform Architect","description":"About NovaSource\n\nNovaSource 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 5 continents, NovaSource has the global reach and strategic capabilities to achieve our clients’ renewables goals around the world.\n\nNovaSource’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. NovaSource’s expertise extends beyond solar and includes battery energy storage systems (BESS), offering a complete suite of services for the evolving renewable energy landscape.\n\nPosition Overview\n\nWe 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.\n\nKey Responsibilities\n\nEnterprise Data Platform Architecture & Engineering\n\nArchitect, build, and continuously improve the enterprise data platform, ensuring reliability, scalability, and maintainability across core business processes and analytics use cases.\nOwn the full data platform lifecycle — from schema design and pipeline architecture to monitoring, performance tuning, and incident response.\nEstablish and enforce data modeling standards, naming conventions, and governance frameworks across all environments.\nImplement policy enforcement points and access controls (data catalogs, encryption, RBAC) to ensure compliance, privacy, and data protection.\n\nAnalytical Data Modeling & Schema Design\n\nDesign, build, and evolve dimensional data models — including star schemas on Azure Databricks — optimized for analytics and reporting.\nDevelop and refine medallion architecture (bronze-silver-gold layers) for efficient data ingestion, transformation, and consumption.\nBalance model simplicity, flexibility, and performance while minimizing redundancy across analytical datasets.\n\nCloud & Big Data Architecture\n\nLead the design and evolution of the Databricks intelligent data platform, enabling scalable big data processing and laying the foundation for AI/ML capabilities.\nArchitect and manage Azure-based infrastructure including Azure SQL, Azure Data Factory, Azure Synapse Analytics, Data Lake, and related services.\nApply data mesh principles across multiple data repositories to enable decentralized, domain-oriented data ownership.\n\nPipeline Optimization & Automation\n\nEnsure 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.\nDesign and implement automation to significantly reduce recurring DBA and operational tasks, minimizing manual intervention.\nDevelop monitoring, alerting, and self-healing mechanisms to proactively maintain platform health and SLA adherence.\nIdentify and resolve bottlenecks, continuously tuning for performance and scalability.\n\nDomain-Specific Solutions\n\nDesign and implement algorithms supporting availability guarantees, contractual agreement calculations, regulatory reporting (e.g., GADS), and other domain-specific requirements.\nServe as Subject Matter Expert (SME) for performance engineering — profiling, tuning, and resolving issues across database and pipeline layers.\n\nAI & Agentic Capabilities Integration\n\nIncorporate AI and agentic capabilities as complementary components of the data platform.\nDesign and evolve secure LLM integration patterns using enterprise LLM gateways to centralize model access, routing, governance, and cost controls.\nLeverage frameworks like Model Context Protocol (MCP) to connect AI applications and agents with enterprise data sources in a secure, governed manner — enabling intelligent, agent-driven data workflows.\n\nDocumentation, Collaboration & Enablement\n\nPartner with business stakeholders, product teams, and engineering groups to translate requirements into scalable data solutions.\nCreate and maintain clear documentation for data architecture, integration processes, and platform best practices in collaboration with the Enterprise Architecture team.\nProvide technical leadership and mentorship within the technology team; establish best practices and participate in design reviews.\nCollaborate with third-party vendors and system integrators on data platform integrations and joint delivery initiatives.\n\nRequired Qualifications\nBachelor’s degree in Computer Science, Data Engineering, Data Science, or a related field.\n10+ years of experience designing and evolving large-scale data analytics platforms, with deep expertise in data integration (ETL/ELT), medallion-tier pipelines, cloud data services, and MLOps.\nDeep expertise in SQL — query optimization, schema design, indexing strategies, stored procedures, and performance tuning across platforms such as Microsoft SQL Server or Azure SQL.\nHands-on experience with Microsoft Azure data services (Azure SQL, Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, Blob Storage).\nProven experience designing and building on Databricks, including Delta Lake, Spark jobs, and cluster management.\nStrong familiarity with data lakehouse architecture and applying data mesh principles across enterprise environments.\nProven experience with: Azure Data Services (Synapse, Data Factory, Data Lake), Delta Lake, Azure Databricks\nSolid understanding of enterprise data governance, security (access controls, data privacy), and data quality best practices.\nDemonstrated success automating DBA and data operations tasks to significantly reduce manual workload.\nExperience working with contractual or regulatory reporting requirements in data-intensive industries (e.g., energy, utilities, or finance).\nStrong communication and interpersonal skills; ability to work effectively with both technical and non-technical stakeholders across multiple concurrent priorities.\n\nPreferred Qualifications\nExperience integrating AI/ML or LLM solutions into data platforms (e.g., Azure Cognitive Services, LLM gateways for multi-provider model integration, or context frameworks like MCP for AI-driven data products).\nExperience with energy sector data systems, including solar forecasting, GADS reporting, or availability guarantee frameworks.\nExperience with DevOps practices for data: CI/CD pipelines for database deployments, infrastructure-as-code (Terraform, Bicep, ARM templates).\nKnowledge of data security, encryption at rest/in transit, and RBAC in cloud environments.\nMicrosoft Certified: Azure Data Engineer Associate or Databricks Certified Data Engineer Professional.\nExperience partnering with third-party data vendors and managing vendor-delivered integrations.\nMaster’s degree in a relevant field.\n\nTechnical Skills Summary\n\nDatabases & SQL: SQL Server, Azure SQL, T-SQL, query optimization, indexing, stored procedures.\n\nCloud Platform: Azure Data Factory, Synapse Analytics, Data Lake, Blob Storage, Azure SQL.\n\nBig Data / AI: Azure Databricks, Apache Spark, Delta Lake, AI/ML pipeline foundations, LLM integration.\n\nArchitecture Patterns: Medallion architecture, data mesh, data warehousing, ETL/ELT, dimensional modeling on Azure Databricks.\n\nAutomation & DevOps: Pipeline automation, CI/CD for data, scripting (Python, PowerShell, or equivalent).\n\nGovernance & Security: Data catalogs, RBAC, encryption, data quality, compliance frameworks.\n\nMonitoring & Ops: Alerting, performance monitoring, incident mitigation, SLA management.\n\nWorking at NovaSource Power Services:\n\nWe value employee life outside of work and provide many ways to accommodate and support our staff in achieving their goals. You'll find a few ways we enact this below:\n\nExperience comes in many forms, many skills are transferable, and passion goes a long way. If the job description gets you pumped but your background isn’t exactly what we’ve described above, or if you strongly believe you bring qualifications beyond what we’ve outlined that would help you excel in this position, please consider applying.\n\nPotential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role.\n\nUS: Diversity Statement – Equal Employment Opportunity\n\nIt is NovaSource’s policy to provide equal employment opportunities to all applicants and employees. NovaSource disapproves of, and will not tolerate, unlawful discrimination against any applicant or employee because of race, color, national origin or ancestry, gender (including pregnancy, childbirth, or related medical conditions), gender identity, age, religion, disability, family care status, veteran status, marital status, sexual orientation, or any other basis protected by local, state or federal laws.","datePosted":"2026-08-22T13:23:53.858Z","dateModified":"2026-08-22T13:23:53.858Z","hiringOrganization":{"@type":"Organization","name":"Novasourcepowerservices","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Chandler","addressRegion":"AZ","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"7dce207a82a580109f6145e0"},"url":"https://jobsearcher.com/jobs/7dce207a82a580109f6145e0"}}