Data Engineer

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
  

AI & Advanced Data Solutions:

• 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
  

Python & Integration Development:

• 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
  

Data Modeling & Analytics Enablement:

• 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
  

Data Integration & Automation:

• 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
  

Data Governance & Collaboration:

• 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
  
  

Requirements:

• 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)

Arhaus is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind. Arhaus is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at Arhaus are based on business needs, job requirements, and individual qualifications, without regard to race, color, sex, sexual orientation, gender identity, religion or belief, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. Arhaus will not tolerate discrimination or harassment based on any of these characteristics. Arhaus encourages applicants of all ages.