Senior Analytics Data Engineer

What you'll do

• Design and deploy end-to-end automated data infrastructure including table schemas and production pipelines for internal and customer-facing products.
• Develop SQL and Python scripts to transform raw source data into high-quality datasets for business products and analysts.
• Implement data quality monitoring procedures, validation rules, and audits to ensure accuracy across all systems.
• Design warehouse architecture and infrastructure to support diverse reporting needs and front-end use cases.
• Build and maintain scalable Power BI solutions to enable self-service analytics for marketing, sales, and product teams.
• Apply data science techniques to curate datasets and develop models that power the front-end user experience.
• Partner with Machine Learning teams to productionize models and implement LLM applications to analyze user behavior.

What we're looking for

• Bachelor's Degree from an accredited, not-for-profit, in-person university or college.
• 5+ years of experience with SQL, Python, PySpark, data warehousing, and business intelligence tools.
• 2+ years of experience with data engineering tools, pipeline creation, and management.
• Experience with cloud computing platforms and data warehouse solutions such as AWS, Azure, Databricks, Snowflake, and Microsoft SQL Server.
• Experience with data visualization tools such as Tableau, Looker, or PowerBI.
• Understanding of AI technologies and hands-on experience leveraging AI tooling in development.
• Experience with Google Analytics (preferred).
• Experience working with large consumer datasets to drive insights and create models (preferred).
• Familiarity with LLMs, prompt engineering, or agent-based architectures (preferred).
• Background in the residential or commercial real estate industry (preferred).