David Weekley Homes is seeking a Senior Data Engineer to support the development, maintenance, optimization, and use of our data infrastructure. We’re looking for a collaborative, well-rounded professional with expertise in building scalable data solutions and enabling data-driven insights. As a key member of our growing data team, you will have significant opportunities to shape our data platform, drive innovation, and support advanced analytics and AI/ML initiatives.We require 3–5 years of experience in data engineering, with a strong preference for expertise in Snowflake. Experience with SQL Server, Azure-based cloud environments, and integrating data across custom in-house systems and third-party SaaS applications is highly valued.Primary Responsibilities:Data Architecture and Modeling: Design, build, and maintain scalable data models, pipelines, and integrations to ensure data reliability and availability.Data Pipeline Development: Develop, optimize, and automate pipelines in Snowflake on Azure; maintain and enhance existing SSIS-based ETL processes where needed.Data Warehouse Management: Manage and optimize Snowflake environments, ensuring performance, scalability, and cost efficiency.Snowflake Advanced Capabilities: Leverage the full suite of Snowflake tools (e.g., semantic modeling, data sharing, Snowpark, and integration with AI/ML platforms) to support advanced analytics, predictive modeling, and enterprise reporting.Cloud & Infrastructure Support: Deploy, monitor, and maintain data systems in Azure, including integrations with Data Factory, Data Lake, and related services.Application Integration: Develop and maintain data flows across custom-built applications and SaaS platforms to ensure data consistency and usability.Data Governance & Quality: Establish and enforce standards for data quality, security, compliance, and lineage; support development and use of comprehensive semantic models.Cross-Team Collaboration: Partner with business stakeholders, analysts, and data scientists to deliver accessible, reliable data for decision-making.Innovation & Best Practices: Research and recommend adoption of emerging tools (e.g., dbt, Airflow) to strengthen our data ecosystem.
