Staff Analytics Engineer

The Nuclear Company is the fastest growing startup in the nuclear and energy space creating a never before seen fleet-scale approach to building nuclear reactors. Through its design-once, build-many approach and coalition building across communities, regulators, and financial stakeholders, The Nuclear Company is committed to delivering safe and reliable electricity at the lowest cost, while catalyzing the nuclear industry toward rapid development in America and globally.

About The Role

The Staff Analytics Engineer is a senior technical role responsible for designing, building, and maintaining the data infrastructure, analytics pipelines, and business intelligence systems that power Nuclear OS. This position combines expertise in data engineering, analytics, and business intelligence to transform raw data into actionable insights that drive decision-making across nuclear construction projects. You'll work at the intersection of data engineering and analytics, building sophisticated data models, ETL/ELT pipelines, and visualization tools that enable predictive analytics, real-time monitoring, and AI-driven optimization for nuclear project delivery.

Key Responsibilities

Data Architecture & Modeling

• Lead the design and implementation of sophisticated data models in data warehouses/lakes, optimizing for performance, scalability, and ease of consumption by analytics tools and data scientists
• Design data storage and analytics systems that support predictive maintenance and business intelligence goals
• Build unified data ontology that creates a "digital twin" of nuclear projects integrating diverse data sources
• Create centralized data lake for all project data including construction performance metrics, quality incidents, schedule deviations, and cost data
• Develop data governance frameworks and quality assurance protocols for enterprise data

Data Pipeline Development

• Develop ingestion pipelines for diverse datasets using ETL/ELT tools (Apache NiFi, Apache Airflow)
• Build automated data pipelines integrating Primavera schedules, BIM models, IoT sensor telemetry, and other sources
• Perform complex data transformations, aggregations, and feature engineering to prepare data for advanced analytics, machine learning, and reporting
• Integrate real-time data from IoT sensors, AR devices, and field operations into analytics systems
• Ensure data quality through validation, cleansing, and monitoring processes

Analytics & Business Intelligence

• Create dashboards and analyses that demonstrate Nuclear OS's value using BI tools (Tableau, PowerBI, Superset)
• Build business intelligence systems for data analysis and decision-making
• Develop analytics tools tailored to project and operational needs
• Drive innovation in complex data visualization and project management interfaces that make nuclear construction data accessible and actionable
• Create standardized performance metrics and reporting frameworks
• Build real-time dashboards with data connectivity for monitoring construction progress and operational performance

AI/ML Support & Predictive Analytics

• Support predictive analytics and machine learning models that learn from historical and real-time data
• Build data pipelines for training and running ML models at scale
• Enable AI-driven predictive analytics for schedule optimization, risk detection, and anomaly identification
• Support AI models for predictive scheduling, ITAAC automation, and risk assessment
• Prepare feature-engineered datasets for data scientists and ML engineers
• Monitor model performance and data drift for production ML systems

Cross-Functional Collaboration

• Work closely with data scientists, principal/senior data engineers, software developers, and business leaders to understand complex data needs and deliver impactful solutions
• Collaborate with engineering, construction, and operations teams to translate business problems into analytics solutions
• Partner with product teams to define analytics requirements and success metrics
• Support regulatory and compliance teams with data-driven insights
• Enable business leaders to make data-driven decisions through accessible analytics

Platform Development & Optimization

• Build analytics infrastructure on Palantir Foundry and associated platforms 17
• Optimize data pipelines for performance, cost, and reliability
• Implement data observability and monitoring systems
• Ensure scalability of analytics systems for fleet-wide deployment
• Develop APIs for analytics services and data access
• Create reusable analytics components and templates

Required Qualifications

Education & Experience

• Bachelor’s degree in computer science, Data Science, Statistics, Engineering, or related field (Master's preferred)
• 7+ years of experience in analytics engineering, data engineering, or business intelligence
• 3+ years working with enterprise data platforms and analytics systems
• Experience in construction, industrial, or complex project environments preferred

Technical Skills - Data Engineering

• Expert proficiency in SQL and database technologies (PostgreSQL, Snowflake, BigQuery, or similar)
• Strong experience with ETL/ELT tools (Apache Airflow, Apache NiFi, dbt, or similar)
• Proficiency in data modeling techniques (dimensional modeling, data vault, etc.)
• Experience with data warehousing and data lake architectures
• Knowledge of data pipeline orchestration and workflow management
• Understanding of data governance, quality, and lineage

Technical Skills - Analytics & BI

• Strong skills in data analysis, statistical modeling, and data visualization tools
• Expert proficiency in BI tools (Tableau, PowerBI, Looker, or similar)
• Experience with business analytics and KPI development
• Knowledge of statistical analysis and A/B testing
• Understanding of data storytelling and visualization best practices

Technical Skills - Programming & Platforms

• Strong programming skills in Python and/or Scala
• Experience with Palantir Foundry or similar enterprise data platforms
• Proficiency in version control (Git) and CI/CD practices
• Knowledge of cloud platforms (AWS, Azure, GCP)
• Familiarity with containerization (Docker, Kubernetes)
• Understanding of API development and microservices

Domain Knowledge

• Understanding of construction project management and workflows
• Knowledge of engineering data, BIM models, and project controls
• Familiarity with IoT data, sensor networks, and real-time analytics
• Awareness of nuclear industry requirements (preferred)
• Understanding of supply chain, procurement, and compliance data

Preferred Qualifications

• Master's degree or Ph.D. in Data Science, Statistics, or related field
• Experience with Palantir Foundry platform
• Background in machine learning and AI systems
• Knowledge of real-time streaming analytics (Kafka, Flink, Spark Streaming)
• Experience with graph databases and network analysis
• Familiarity with blockchain and distributed ledger data
• Certifications in data engineering or analytics (AWS, GCP, Databricks)
• Experience in nuclear, energy, or highly regulated industries

Benefits

• Competitive compensation packages
• 401k with company match
• Medical, dental, vision plans
• Generous vacation policy, plus holidays

Estimated Starting Salary Range
The estimated starting salary range for this role is $150,000 - $173,000 annually less applicable withholdings and deductions, paid on a bi-weekly basis. The actual salary offered may vary based on relevant factors as determined in the Company’s discretion, which may include experience, qualifications, tenure, skill set, availability of qualified candidates, geographic location, certifications held, and other criteria deemed pertinent to the particular role.

EEO Statement
The Nuclear Company is an equal opportunity employer committed to fostering an environment of inclusion in the workplace. We provide equal employment opportunities to all qualified applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We prohibit discrimination in all aspects of employment, including hiring, promotion, demotion, transfer, compensation, and termination.