Analytics Engineer: Semantic Data Architect for Snowflake

Motion Recruitment; Scottsdale (AZ); On-site; USD 120,000 - 170,000; Full time

Job summary

Motion Recruitment is seeking an Analytics Engineer to own the semantic layer and data mart strategy that connects SAP-replicated data to business teams relying on it. You will build clean, tested dbt models in Snowflake and design semantic models queryable by BI tools and LLMs.

You will leverage AI coding assistants to accelerate model development while maintaining rigorous review, ensuring speed and quality in production. Collaboration with SAP teams and data engineers is essential.

Qualifications

• 3+ years in analytics/data/BI engineering delivering production dbt models at scale.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or related quantitative field.
• Proficiency in dbt Core/Cloud staging/intermediate/mart layer patterns, incremental models, tests, documentation.
• Working knowledge of Snowflake concepts and SQL performance tuning.
• Python proficiency for test development and automation.

Responsibilities

• Own the semantic layer and data mart strategy connecting SAP data to business teams.
• Build and test dbt models for SAP-replicated data in Snowflake.
• Define governance, metadata, and data dictionary for analytical assets.
• Collaborate with SAP, Data Engineers, and analysts on data marts and dashboards.
• Optimize data mart performance for Hex workbooks and finance dashboards.
• Enable self-service analytics through clean datasets.

Skills

dbt

Snowflake

SQL

Python

Git & CI/CD

AI tools usage

Education

Bachelor's degree

Tools

dbt-utils

dbt-expectations

GitLab CI

Azure DevOps

Job description

Motion Recruitment is seeking an Analytics Engineer to own the semantic layer and data mart strategy that connects SAP-replicated data to business teams relying on it. You will build clean, tested dbt models in Snowflake and design semantic models queryable by BI tools and LLMs.

You will leverage AI coding assistants to accelerate model development while maintaining rigorous review, ensuring speed and quality in production. Collaboration with SAP teams and data engineers is essential.