Lead Data Architect - Utilities Experience

We are seeking a Data Modeling Expert with strong AI/Analytics focus to enable next-generation data platforms supporting predictive analytics, machine learning, and intelligent automation. This role will design and optimize data models that power use cases such as grid reliability, predictive maintenance, wildfire risk modeling, customer analytics, and AI-driven operations.Key ResponsibilitiesDesign AI-ready data models to support machine learning, advanced analytics, and real-time decisioningBuild and maintain feature-ready datasets for data science teams (feature engineering support)Develop semantic and analytical data layers for BI, AI, and self-service analyticsCollaborate with data scientists to translate ML use cases into scalable data structuresModel and integrate high-volume time-series and IoT data (e.g., smart meters, sensors, grid telemetry)Enable real-time / near-real-time data pipelines for AI-driven insightsEnsure data models support MLOps frameworks (model training, validation, deployment pipelines)Implement data lineage, observability, and quality frameworks to support trusted AI outcomesOptimize data structures for lakehouse architectures and distributed compute environmentsAlign with data governance, privacy, and regulatory compliance requirementsAI/Analytics Use Case AlignmentPredictive Maintenance: Asset failure prediction using sensor and maintenance dataWildfire Risk Modeling: Environmental and grid data modeling for risk forecastingLoad Forecasting: Time-series modeling for energy demand predictionCustomer 360 Analytics: Behavioral segmentation and usage insightsGrid Intelligence: AI-driven outage prediction and response optimizationGenerative AI Enablement: Structuring enterprise data for LLM-based insights and copilotsRequired Qualifications8+ years in data modeling, data architecture, or analytics engineering3+ years of Utility/energy domain experience (smart grid, AMI, SCADA systems) supporting electric, gas, and/or water utilities.Strong expertise in:Dimensional modeling for analytics (Star/Snowflake schemas)Data modeling for machine learning pipelinesSQL and data transformation frameworks (dbt preferred)Experience designing data models for:Data lakes / lakehouse architectures (Delta Lake, Iceberg, etc.)Structured + semi-structured data (JSON, Parquet)Proven experience supporting AI/ML workloads in production environmentsPreferred QualificationsExperience with cloud AI ecosystems:AWS (SageMaker, Redshift)Azure (Synapse, Azure ML)GCP (BigQuery, Vertex AI)Familiarity with time-series and streaming platforms (Kafka, Spark Streaming)Knowledge of feature stores (Feast, Tecton)Experience with MLOps tools (MLflow, Kubeflow)Understanding of LLM data preparation, vector databases, and embeddingsKey SkillsAI/ML Data Modeling & Feature EngineeringLakehouse & Modern Data Stack (dbt, Spark, Delta Lake)Time-Series & Streaming Data ModelingData Governance for AI (quality, lineage, bias mitigation)Performance Optimization for Analytics WorkloadsCross-functional collaboration (Data Science, Engineering, Business)