Analytics Engineer

• 5+ years of experience in analytics engineering, data engineering, or advanced BI within a modern data stack
• Strong SQL skills with experience building scalable, well-structured datasets
• Hands-on experience with dbt (or similar) for modeling, testing, and documentation
• Experience working with cloud data warehouses (Snowflake preferred), including performance tuning and cost awareness
• Solid understanding of analytics engineering best practices:

• Star and snowflake schemas
• Incremental models
• Fact/dimension modeling
• Medallion architecture

• Experience working in a CI/CD environment (version control, code reviews, deployments)
• Proven ability to partner with operations teams to turn business needs into reliable data models and reporting
• Bachelor's degree in Analytics, Engineering, Computer Science, or related field (or equivalent experience), * Experience supporting critical facilities, facilities operations, or manufacturing operations
• Strong understanding of operational data, including:

• Capacity, utilization, and availability metrics
• Asset performance, uptime/downtime, and maintenance data
• Work orders, incident tracking, and operational KPIs
• Forecasting, planning, and variance analysis tied to operations

• Experience working with data from CMMS, IoT systems, or operational platforms
• Ability to design and support operational dashboards and reporting used by:

• Facilities leadership
• Operations and engineering teams
• Capacity and planning teams

• Comfortable working with incomplete or evolving operational data, building trust through validation and consistent modeling

Commercial Real Estate / Data Center Experience (Strong Preference)

• Experience in data centers, critical facilities, or asset-heavy environments strongly preferred
• Familiarity with:

• Site, building, campus, and regional hierarchies
• Capacity constraints (power, space, cooling, etc.)
• Utilization and availability tracking

• Experience modeling data across multiple physical and operational layers
• Ability to align analytics with real-world operational constraints is a strong plus, * Advanced SQL and strong data modeling skills
• dbt (models, tests, macros, documentation)
• Snowflake (query optimization, usage patterns, access controls)
• Experience integrating data from SaaS and operational systems using ELT tools (Fivetran, Stitch, etc.)
• Familiarity with data quality, metadata management, and lineage

Professional & Communication Skills

• Strong business understanding with the ability to frame data in operational and facilities context
• Clear communicator who can work with:

• Facilities and operations teams
• Engineering and maintenance teams
• Data engineering and platform teams

• Ability to create clear, usable documentation for data models and metrics
• High attention to detail with a focus on accuracy, consistency, and reliability
• Comfortable working in complex environments with multiple upstream systems