What are the responsibilities and job description for the Data Engineer position at Arhaus?
Job Details
Description
Arhaus was founded in 1986 on a simple idea: Furniture and décor should be sustainably sourced, lovingly made, and built to last. Today, we partner with artisans around the world who share our vision, creating beautiful, heirloom-quality pieces that can be used—and loved—for generations.
Description:
The Data Engineer is responsible for designing, building, and optimizing scalable data platforms and AI-driven solutions. This role plays a critical part in advancing a modern, Snowflake-first data architecture, with a strong emphasis on AI agent implementation, data pipeline automation, and advanced analytics enablement.
This individual will partner cross-functionally with business, analytics, and technology teams to deliver high-impact data and AI capabilities that support business decision-making and operational efficiency.
Essential Duties & Responsibilities:
This role is focused on modern data engineering and AI integration within a cloud-based ecosystem. Key responsibilities include:
Data Engineering & Snowflake:
Description
Arhaus was founded in 1986 on a simple idea: Furniture and décor should be sustainably sourced, lovingly made, and built to last. Today, we partner with artisans around the world who share our vision, creating beautiful, heirloom-quality pieces that can be used—and loved—for generations.
Description:
The Data Engineer is responsible for designing, building, and optimizing scalable data platforms and AI-driven solutions. This role plays a critical part in advancing a modern, Snowflake-first data architecture, with a strong emphasis on AI agent implementation, data pipeline automation, and advanced analytics enablement.
This individual will partner cross-functionally with business, analytics, and technology teams to deliver high-impact data and AI capabilities that support business decision-making and operational efficiency.
Essential Duties & Responsibilities:
This role is focused on modern data engineering and AI integration within a cloud-based ecosystem. Key responsibilities include:
Data Engineering & Snowflake:
- Design, develop, and optimize data pipelines, models, and workflows using Snowflake
- Manage large-scale data ingestion, transformation, and processing pipelines (ETL/ELT)
- Ensure data quality, reliability, performance, and scalability across platforms
- Develop and implement AI agents and AI-driven workflows using Snowflake (Cortex)
- Integrate structured and unstructured data sources to support AI use cases such as automation and document processing
- Build orchestration logic for AI pipelines and workflows
- Build and maintain data pipelines and automation solutions using Python
- Develop integrations with APIs, external systems, and AI services
- Implement data transformation, validation, and processing logic
- Design and maintain scalable data models aligned with data warehousing best practices (OLAP/EDW)
- Write and optimize SQL queries across Snowflake and SQL Server environments
- Support downstream analytics, reporting, and business intelligence initiatives
- Build scalable ingestion frameworks, including batch and API-based solutions
- Automate workflows to support data movement and AI processing
- Integrate enterprise systems into a unified data ecosystem
- Support data governance, security, and compliance best practices
- Partner with analysts, business stakeholders, and leadership to translate requirements into technical solutions
- Document data architecture, pipelines, and AI workflows
- 3 years of experience working with Snowflake
- 5 years of experience with SQL and SQL Server
- 5 years of experience in data engineering, data modeling, or data pipeline development
- 2 years of experience with Python programming
- 2 years of experience developing or implementing AI/ML solutions or AI agents
- Strong experience with ETL/ELT processes, API integrations, and data pipeline architecture
- Solid understanding of data warehousing concepts (OLAP, EDW)