Staff Analytics Engineer

Description

• Ensure scalability of analytics systems for fleet-wide deployment
• Establish analytics engineering standards and best practices
• Lead code reviews and technical design discussions
• Develop ingestion pipelines for diverse datasets using ETL/ELT tools (Apache NiFi, Apache Airflow)
• Implement data observability and monitoring systems
• Enable business leaders to make data-driven decisions through accessible analytics
• Create centralized data lake for all project data including construction performance metrics, quality incidents, schedule deviations, and cost data
• Create dashboards and analyses that demonstrate Nuclear OS's value using BI tools (Tableau, PowerBI, Superset)
• Support predictive analytics and machine learning models that learn from historical and real-time data
• Develop analytics tools tailored to project and operational needs
• Partner with product teams to define analytics requirements and success metrics
• Drive innovation in complex data visualization and project management interfaces that make nuclear construction data accessible and actionable
• Perform complex data transformations, aggregations, and feature engineering to prepare data for advanced analytics, machine learning, and reporting
• Enable AI-driven predictive analytics for schedule optimization, risk detection, and anomaly identification
• Drive continuous improvement in analytics processes and tools
• Develop data governance frameworks and quality assurance protocols for enterprise data
• Develop APIs for analytics services and data access
• Monitor model performance and data drift for production ML systems
• Share knowledge through documentation and training
• Build real-time dashboards with data connectivity for monitoring construction progress and operational performance
• Optimize data pipelines for performance, cost, and reliability
• Provide technical guidance and mentorship to junior analytics engineers, fostering their growth and ensuring adherence to best practices
• Build data pipelines for training and running ML models at scale
• Design data storage and analytics systems that support predictive maintenance and business intelligence goals
• Support regulatory and compliance teams with data-driven insights
• Integrate real-time data from IoT sensors, AR devices, and field operations into analytics systems
• Build automated data pipelines integrating Primavera schedules, BIM models, IoT sensor telemetry, and other sources
• Work closely with data scientists, principal/senior data engineers, software developers, and business leaders to understand complex data needs and deliver impactful solutions
• Create reusable analytics components and templates
• 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
• Collaborate with engineering, construction, and operations teams to translate business problems into analytics solutions
• Prepare feature-engineered datasets for data scientists and ML engineers
• Support AI models for predictive scheduling, ITAAC automation, and risk assessment
• Build analytics infrastructure on Palantir Foundry and associated platforms 17
• Create standardized performance metrics and reporting frameworks
• Build business intelligence systems for data analysis and decision-making
• Build unified data ontology that creates a "digital twin" of nuclear projects integrating diverse data sources
• Ensure data quality through validation, cleansing, and monitoring processes

Requirements

• Certifications in data engineering or analytics (AWS, GCP, Databricks)
• Excellent communication skills to explain complex data concepts to technical and non-technical stakeholders
• Strong experience with ETL/ELT tools (Apache Airflow, Apache NiFi, dbt, or similar)
• Experience with data warehousing and data lake architectures
• Experience with graph databases and network analysis
• Knowledge of statistical analysis and A/B testing
• Experience with Palantir Foundry or similar enterprise data platforms
• Expert proficiency in BI tools (Tableau, PowerBI, Looker, or similar)
• Proficiency in data modeling techniques (dimensional modeling, data vault, etc.)
• 3+ years working with enterprise data platforms and analytics systems
• Strategic thinking to align analytics with business objectives
• Experience with business analytics and KPI development
• Familiarity with containerization (Docker, Kubernetes)
• Collaborative mindset to work across teams and functions
• 7+ years of experience in analytics engineering, data engineering, or business intelligence
• Ability to work independently and lead analytics initiatives
• Awareness of nuclear industry requirements (preferred)
• Experience in construction, industrial, or complex project environments preferred
• Master's degree or Ph.D. in Data Science, Statistics, or related field
• Understanding of supply chain, procurement, and compliance data
• Knowledge of cloud platforms (AWS, Azure, GCP)
• Understanding of data governance, quality, and lineage
• Knowledge of engineering data, BIM models, and project controls
• Understanding of data storytelling and visualization best practices
• Familiarity with IoT data, sensor networks, and real-time analytics
• Bachelor’s degree in computer science, Data Science, Statistics, Engineering, or related field (Master's preferred)
• Familiarity with blockchain and distributed ledger data
• Experience with Palantir Foundry platform
• Knowledge of real-time streaming analytics (Kafka, Flink, Spark Streaming)
• Experience in nuclear, energy, or highly regulated industries
• Understanding of API development and microservices
• Strong skills in data analysis, statistical modeling, and data visualization tools
• Expert proficiency in SQL and database technologies (PostgreSQL, Snowflake, BigQuery, or similar)
• Understanding of construction project management and workflows
• Strong programming skills in Python and/or Scala
• Background in machine learning and AI systems
• Knowledge of data pipeline orchestration and workflow management
• Proficiency in version control (Git) and CI/CD practices

Benefits

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

Training + Development

Interview process

Visa Sponsorship

Security clearance