Data Engineer 2 (Full-Time) - Special Projects Department

The Church of Jesus Christ of Latter-day Saints • Salt Lake, UT

2d

About The Position

Design and maintain scalable data solutions that enable analytics, AI-driven insights, and decision-making across temple construction and operations . This role combines data engineering and analytics engineering , supporting data pipelines, AI-ready datasets, and business-ready insights in partnership with business operations teams

Requirements

• Bachelor’s degree in a related field or equivalent field experience
• 3–5 years in data engineering, analytics engineering, or related field, supporting property development and facility operations data
• Experience working with AI/ML concepts, data preparation for models, or supporting predictive analytics use cases
• SQL (advanced querying, transformations, performance tuning)
• Python (or similar) for data processing, automation, and basic ML integration
• ETL/ELT pipeline development (batch and/or streaming)
• Cloud data platforms (AWS, Azure, or GCP)
• Data modeling (dimensional/star schema)
• Data transformation frameworks (e.g., dbt or similar)
• BI and reporting tools (Power BI, Tableau, or similar)
• Exploratory data analysis (EDA), KPI/metric development, and AI-ready

Responsibilities

• Build and maintain data pipelines from project and property systems
• Support cloud data platforms and data storage environments
• Organize data to support reporting across assets and projects
• Combine and structure data from development, construction, and operations
• Create and improve dashboards and reports for tracking performance (Power BI, Tableau etc.)
• Work with construction and facilities teams to deliver data solutions
• Ensure data is accurate, consistent, and reliable
• Improve data processes for speed and efficiency
• Support lifecycle data tracking (design → construction → operations → maintenance)
• Establish documentation, standards, and data engineering best practices
• Prepare clean, usable datasets for analytics and AI use
• Perform exploratory data analysis to identify trends, anomalies, and insights
• Help define and standardize key performance metrics (KPIs)
• Collaborate on predictive and AI use cases (e.g., maintenance, cost, energy forecasting)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees