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Valon is an AI-native platform for mortgage servicing, powering 1 in 6 U.S. mortgages across major servicers like Newrez, Carrington, and ServiceMac. The company recently raised $150M Series D at a $2.3B valuation and is building the operating system to replace legacy mainframe systems in regulated finance.
As Senior Analytics Engineer, you will own the client reporting data models and pipelines that transform raw data into reliable, structured, performant assets for reporting, analysis, and AI initiatives. This role sits at the intersection of analytics and data engineering, ensuring data is production-grade, auditable, and accessible across the organization and customers.
Key responsibilities include:
- Scoping and developing new client reports while maintaining and enhancing existing reporting pipelines; collaborating with external clients and internal client success teams to manage inbound requests
- Designing, building, and maintaining production-grade data models and analytical layers using BigQuery, dbt, and Airflow at scale
- Partnering with engineering and product teams to define and implement data contracts and observability frameworks for data quality and auditability in a regulated environment
- Writing complex SQL queries, building dashboards in Hex or Looker, and conducting ad hoc analysis to empower operational leaders with root-cause insights
You will standardize data modeling practices, manage orchestration of analytical workflows, and provide hands-on analytical support for high-stakes operational business functions including reporting and performance management.
REQUIREMENTS:
- 7+ years of combined experience in data engineering, analytics engineering, or highly technical data analytics role, ideally at a technology company or financial institution (Series B–E startup experience is a plus)
- Expertise in SQL (required); strong proficiency in Python
- Proven experience with modern data stack tools: dbt and Airflow
- Deep understanding of data architecture patterns (e.g., medallion architecture) and experience implementing data quality frameworks, observability tools, or data contracts at scale
- Experience with data visualization tools (Hex, Looker, or equivalent) and proficiency in Google Sheets/Microsoft Excel
- Ability to communicate effectively with external clients, synthesizing requests, establishing realistic timelines, and managing expectations
- Strong product mindset focused on usability, reliability, and developer experience of data systems
- Proven ability to solve complex problems independently and build repeatable processes
- Bachelor's degree or equivalent professional experience in Computer Science, Data Analytics, or similar field
