Releady is partnering with a leading furniture and home furnishings retail company to hire a Data Engineer. This organization is the top-selling furniture brand in North America and is undergoing an AI-first technology transformation, modernizing its data platform to support advanced analytics, machine learning, and business intelligence across a growing retail footprint. The role sits within a Technology and AI Center of Excellence spanning cloud, data, security, and automation.
In this role, you will design, build, and maintain scalable, high-performance data pipelines and infrastructure that power the company's analytics and machine learning initiatives. The work operates primarily within a Microsoft Fabric and Azure ecosystem, driven by Python and PySpark. You will collaborate closely with AI/ML engineers, BI teams, developers, and business stakeholders to ensure data is reliable, accessible, and optimized for downstream use, while contributing directly to the re-architecture and modernization of the company's data platform.
Data Pipeline Development & Management
• Design, build, and optimize ETL/ELT notebooks and pipelines for ingestion, transformation, and delivery of business-critical data.
• Implement medallion architecture (bronze, silver, and gold layers) to standardize data for downstream consumption.
• Automate data collection, processing, and reporting workflows to improve efficiency and reduce manual effort.
• Ensure high-quality, reliable data through validation, monitoring, troubleshooting, and performance tuning.
• Integrate APIs, data flows, and orchestration processes across the Microsoft ecosystem.
Collaboration & Analytics Enablement
• Partner with AI/ML engineers, BI teams, developers, and business stakeholders to structure data for analytics, forecasting, and ML initiatives.
• Contribute to the re-architecture and modernization of the company's data platform for scalability and business alignment.
• Maintain clear documentation of data models, pipelines, and integrations for transparency and knowledge sharing.
Data Quality & Governance
• Implement systems to monitor data quality, ensure data integrity, and enforce security standards.
• Audit, track, and improve data processes to comply with organizational standards and regulatory requirements.
• Support version control, Agile workflows, and best practices using Git, Jira, and Confluence.
• Bachelor's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience as a Data Engineer or in backend or data-intensive systems.
• Expertise in ETL/ELT design, data integration, and pipeline orchestration.
• Proficiency in SQL and Python for data processing and automation.
• Hands-on experience with the Microsoft stack: Fabric, Azure, Python, PySpark notebooks, Data Factory, Data Lakes, and SQL Server.
• Familiarity with medallion architecture (bronze, silver, and gold) and modern data warehouse practices.
• Knowledge of data modeling, version control (Git), and Agile tools (Jira, Confluence).
• Preferred: experience with AI/ML applications, SQL database administration, and a strong statistical foundation to support data-driven modeling.