Analytics Engineer - dbt / Snowflake

Analytics Engineer dbt / Snowflake

Location: Scottsdale, AZ (Hybrid Tuesday Thursday onsite)



Alternate Location: San Diego, CA



Contract: 12+ months







Industry: Energy / Utilities

Job Overview

We are seeking an experienced Analytics Engineer to join a data modernization initiative focused on replicating enterprise data into Snowflake and building business-ready analytical data marts and semantic models.

The ideal candidate will have strong hands-on experience with dbt Core, Snowflake, advanced SQL, and analytical data modeling . This role will focus on transforming raw data into clean, reliable, well-documented datasets that support business intelligence, self-service analytics, and AI-powered conversational use cases.

You will work closely with Data Engineers, SAP SMEs, business stakeholders, and analysts to understand business requirements, define data models, and deliver high-quality analytical solutions.

Key Responsibilities

dbt & Data Modeling

• Develop and maintain production-grade dbt models across staging, intermediate, and mart layers.
• Transform raw operational and financial data into clean, tested, and business-ready analytical datasets.
• Design dimensional models, fact and dimension tables, and appropriate data relationships and grain.
• Implement incremental models, reusable macros, and dbt packages.
• Develop comprehensive data quality tests, including generic, singular, and referential integrity tests.
• Maintain model documentation, data dictionaries, and lineage.

Snowflake Development

• Build and optimize analytical datasets within Snowflake.
• Apply SQL optimization techniques and cost-aware data modeling practices.
• Work with large datasets and design efficient queries and transformations.
• Support reliable and scalable data marts for reporting and self-service analytics.

Semantic Layer & AI-Ready Analytics

• Build and maintain semantic views or semantic models that define business metrics, dimensions, and relationships.
• Structure analytical models with consistent naming conventions, clear definitions, and appropriate metadata.
• Develop datasets that enable BI tools and LLM-powered conversational analytics to answer business questions accurately.
• Collaborate with analysts and AI solution teams to improve the usability of analytical data.

Business Partnership & Requirements Gathering

• Work directly with business stakeholders and SMEs to understand data requirements and business rules.
• Translate business questions into scalable data models and transformation logic.
• Conduct data model walkthroughs and explain technical decisions to both technical and non-technical audiences.
• Validate model outputs and ensure alignment with business definitions and reporting requirements.

Collaboration & Engineering Practices

• Partner with Data Engineers on source data structures, ingestion dependencies, and data contracts.
• Collaborate with analysts on analytical datasets and self-service reporting.
• Use Git-based workflows, code reviews, and CI/CD practices for dbt development.
• Use AI coding assistants such as Claude Code, ChatGPT, or GitHub Copilot when appropriate, applying sound technical judgment and reviewing generated code for accuracy, security, and quality.

Required Qualifications

• 3+ years of experience in Analytics Engineering, Data Engineering, BI Engineering, or a related role.
• Strong hands-on experience developing production dbt models, preferably with dbt Core.
• Strong Snowflake experience in analytical data development.
• Excellent data modeling skills, including transforming raw source data into business-ready data marts.
• Advanced SQL skills, including CTEs, window functions, complex transformations, and query optimization.
• Experience with semantic views, semantic models, or metric definitions for BI and/or AI-powered analytics.
• Experience gathering requirements and working directly with business stakeholders or SMEs.
• Strong communication, analytical thinking, and problem-solving skills.
• Ability to work independently, manage priorities, and take ownership of deliverables.
• Experience with Git, code reviews, and production development workflows.
• Python experience for scripting, automation, or custom data quality testing.

Preferred Qualifications

• Experience with Snowflake semantic models, Cortex Analyst, or dbt Semantic Layer / MetricFlow.
• Experience developing analytical datasets for BI tools such as Hex, Tableau, Power BI, or similar platforms.
• Experience with dbt packages such as dbt-utils and dbt-expectations.
• Exposure to Dagster or other orchestration platforms.
• Experience working with financial, operational, procurement, inventory, or asset-management data.
• Energy, utilities, financial services, or other enterprise data experience.
• Experience with SAP ERP data or collaboration with SAP SMEs.
• Familiarity with Snowflake Cortex or LLM-assisted development workflows.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.

What We Are Looking For

We are looking for an Analytics Engineer who combines strong technical modeling expertise with excellent communication and business understanding. The successful candidate should be able to independently take raw data and business requirements, design the appropriate dbt and Snowflake models, and deliver reliable, consumable datasets.

SAP expertise and specific AI-tool experience are not required. Candidates should have strong dbt, Snowflake, data modeling, semantic layer, and stakeholder collaboration experience is required.