Senior Data Science, AI & Analytics Engineer

Clean Energy Fuels is North America's largest provider of renewable natural gas and alternative fueling solutions for the transportation industry. They are seeking a Senior Data Science, AI & Analytics Engineer to design, develop, and support AI and analytics solutions that enhance operational performance and decision-making across the organization.

Responsibilities:

• Design, develop, and maintain scalable data pipelines, enterprise data products, APIs, integrations, and analytics solutions using Azure Databricks, SQL, Python, and cloud-based technologies
• Develop and support data integration frameworks connecting ERP systems, operational platforms, financial applications, IoT devices, external systems, and third-party data providers
• Design and maintain secure API-based integrations that enable efficient data exchange across enterprise applications and business processes
• Develop trusted, reusable, and governed datasets that support reporting, analytics, AI, automation, and operational intelligence initiatives
• Implement modern data engineering practices including data quality validation, automated testing, monitoring, observability, lineage tracking, and performance optimization
• Improve scalability, reliability, maintainability, and security of enterprise data and analytics platforms
• Modernize manual, spreadsheet-based, and legacy business processes through automation and cloud-based solutions
• Design, develop, and support AI-enabled solutions that improve productivity, operational efficiency, and business decision-making
• Build intelligent automation workflows using Generative AI, machine learning, AI agents, APIs, workflow orchestration, and enterprise data platforms
• Develop AI-powered assistants, custom copilots, recommendation engines, knowledge solutions, and decision-support capabilities
• Integrate AI services and intelligent automation into enterprise applications, reporting solutions, and operational workflows
• Develop predictive analytics, intelligent auditing, anomaly detection, forecasting, optimization, and recommendation solutions
• Identify opportunities to reduce manual effort through automation and AI-driven process transformation
• Collaborate with business stakeholders to evaluate, prioritize, and implement high-value AI initiatives
• Support AI governance, monitoring, testing, and continuous improvement to ensure scalable and responsible AI adoption
• Design and support data pipelines and analytics solutions that leverage IoT, telemetry, operational, and industrial data sources
• Develop near real-time operational monitoring, alerting, and intelligence capabilities that improve visibility into business and field operations
• Support predictive maintenance, condition-based monitoring, asset performance management, and operational optimization initiatives
• Build scalable streaming and event-driven data solutions capable of processing high-volume operational and telemetry data
• Develop dashboards, analytics, and operational intelligence solutions that provide visibility into asset health, utilization, reliability, performance trends, and business KPIs
• Collaborate with Operations, Engineering, and business teams to identify opportunities to improve efficiency, reduce downtime, and optimize performance through data, AI, and automation
• Support the evolution of connected asset, digital operations, and industrial intelligence capabilities across Clean Energy's fueling and operational network
• Support enterprise data governance, reporting certification, and data quality initiatives
• Develop automated monitoring, validation, reconciliation, and exception-reporting capabilities
• Assist with metadata management, lineage tracking, documentation, and governance practices
• Partner with business stakeholders to improve the accuracy, consistency, reliability, and trustworthiness of enterprise data assets
• Power BI development
• Semantic model and dataset development
• DAX and Power Query
• Dashboard design and optimization
• Reporting automation and self-service analytics
• Translate business requirements into practical and scalable technical solutions
• Participate in all phases of solution delivery including discovery, design, development, testing, deployment, and production support
• Collaborate closely with cross-functional teams to ensure solutions align with business objectives
• Contribute to technical documentation, knowledge sharing, and continuous improvement initiatives

Requirements:

• 7–10+ years experience
• Enterprise-scale data platforms
• Cloud analytics architecture
• API integration development
• Advanced SQL and Python
• Power BI administration and governance experience
• PySpark and distributed processing experience
• Data governance and data quality experience
• Experience supporting AI and machine learning solutions
• IoT, telemetry, or operational analytics experience
• Experience with enterprise data modernization initiatives