Analytics Engineer

Summary

Job Summary for Analytics Engineer SAP to Snowflake Initiative

• Contract Duration: 12 months
• Location: Scottsdale, AZ (strongly preferred) or San Diego, CA (alternative); Hybrid schedule (onsite Tues Thurs)
• Industry Domain: Energy, utilities, or renewable power
• Team Structure: Work alongside Data Engineer, 2 Data Analysts, AI Solutions Architect, and business/SAP SMEs
  
  

Primary Responsibilities

• Lead the design, development, and maintenance of dbt data models transforming SAP (ERP) data replicated into Snowflake into business-ready marts and semantic models.
• Own the semantic/modeling layer collaborate with Data Engineers (who own ingestion and pipelines) and business SMEs to translate raw/source data into consumable analytics assets.
• Build, test, and document dbt models for financial, operational, and asset management data; ensure data quality and integrity through tests, constraints, and documentation.
• Develop and maintain Snowflake semantic models and views supporting analytics, self-service BI, and conversational AI (LLM) use cases.
• Partner with business stakeholders (Finance, Accounting, Asset Management, Trading, etc.) to gather requirements, clarify business logic, and deliver solutions aligned to business needs.
• Enable Hex dashboards and self-service analytics by building and optimizing data marts for dashboard performance and usability.
• Implement and maintain data quality, governance, lineage, and documentation standards for all analytical assets.
• Use AI coding assistants (Claude, ChatGPT Codex, Copilot) to accelerate model building, while applying critical review and ensuring responsible AI practices.
• Support enablement and training for analysts and business users, including walkthroughs, documentation, and data dictionaries.
• Participate in cross-functional collaboration work closely with Data Engineers, Data Scientists, Analysts, and business partners.
  
  

Key Skills/Experience

• 3 years in Analytics Engineering/Data Engineering/BI Engineering roles with production dbt model delivery
• Strong hands-on experience with dbt (dbt Core preferred), including staging/intermediate/mart layers, macros, tests, and documentation
• Advanced skills in Snowflake (query optimization, clustering, time travel, etc.)
• Excellent data modeling capabilities for transforming raw data to business-ready marts and semantic views
• Advanced SQL and Python skills for modeling, testing, and automation
• Strong communication and requirements gathering; ability to work directly with business and technical stakeholders
• Experience building datasets for BI tools (Hex experience a plus)
• Familiarity with AI/LLM-assisted workflows and semantic data models for AI/BI consumption
  
  

Nice To Have

• dbt Analytics Engineer certification
• Experience with Snowflake semantic models (Cortex Analyst) or dbt Semantic Layer/MetricFlow
• Exposure to Dagster or orchestration platforms
• Industry experience in energy, utilities, or financial services
• Knowledge of data governance, compliance, and regulatory frameworks (SOX, GDPR, CCPA)
• Experience with Snowflake Cortex (LLM functions, ML-powered features)
  
  

Summary Statement

You will be responsible for transforming and modeling SAP data replicated into Snowflake, building business-ready, AI/BI-consumable data marts and semantic models using dbt, and enabling advanced analytics and self-service for an energy/utility domain client. This role requires strong technical skills (dbt, Snowflake, SQL, Python), excellent communication, and the ability to partner with both technical teams and business stakeholders.