Analytics Engineer: Semantic AI Data Foundations

Nimble Gravity, LLC; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Nimble Gravity, LLC is hiring Analytics Engineers to blend insurance domain expertise with full‑stack data and analytics capabilities. You will craft trusted data, governance, and semantic layers powering AI agents, while collaborating with LOB teams to shape the next data products.

You will design robust data models, build pipelines, and ensure data is structured, governed, and ready for AI-driven insights. This role blends hands‑on engineering with strategic signal for future work.

Qualifications

• Strong SQL skills with advanced patterns and window functions.
• Experience building data infrastructure and pipelines.
• Proficient in dbt projects with testing and CI/CD.
• Python-based data pipelines and automation experience.
• Ability to translate business needs into technical specs.

Responsibilities

• Architect flexible, high-performance data models across domains.
• Build data pipelines using SQL, Python, dbt, and Snowflake.
• QA data and implement automated tests for data models.
• Contribute to data governance: permissions, lineage, definitions.
• Design data security to restrict access to sensitive data.
• Develop semantic models for natural language queries.
• Define metrics/relationships for AI agent reasoning.
• Document templates, run workshops, and share playbooks.
• Create semantic views and YAML/Markdown configs for analysts.

Skills

Advanced SQL

Analytics engineering

dbt

Python

Semantic modeling

Snowflake

Data governance

Client-facing communication

Git

Airflow

Tools

dbt

Snowflake

Python

Git

Airflow

Job description

Nimble Gravity, LLC is hiring Analytics Engineers to blend insurance domain expertise with full‑stack data and analytics capabilities. You will craft trusted data, governance, and semantic layers powering AI agents, while collaborating with LOB teams to shape the next data products.

You will design robust data models, build pipelines, and ensure data is structured, governed, and ready for AI-driven insights. This role blends hands‑on engineering with strategic signal for future work.