Senior Analytics Engineer

About the Company

Valon is transforming both mortgage servicing and consumer direct lending with a technology-first approach. Backed by Andreessen Horowitz (a16z) and managing over $130 billion in loans, we’ve built our platforms from the ground up—not on outdated legacy systems—so homeowners, lenders, and investors experience greater transparency, efficiency, and care. By unifying processes into a modern, AI-native operating system, we’re leading the way in automation, compliance, and continuous improvement across our servicing and lending businesses.

Our mission is to empower every homeowner by making the mortgage experience simple, secure, and financially empowering. To achieve this, we bring together world-class engineers, servicing experts, lending professionals, and operations leaders who share a passion for improving the homeowner journey. We’re not only reshaping what servicing and lending look like today—we’re creating opportunities for talented people to help drive the future of the industry.

As we continue to grow, Valon is expanding its footprint across multiple states, opening the door to exciting new roles and career paths. Joining Valon means becoming part of a fast-scaling company where innovation, collaboration, and customer impact go hand in hand. Mortgage is just the beginning—we’re building the future of regulated finance, and we want you to be part of it.

About the Role

We are seeking a Senior Analytics Engineer to take ownership of our external client reporting pipelines. This crucial role involves managing the layer of our data platform responsible for transforming raw data into reliable, structured, and performant assets for reporting, analysis, and AI initiatives. This role sits at the intersection of engineering and analytics, ensuring data is production-grade, auditable, and easily accessible across the organization.

You will own client reporting, standardize our data modeling practices, manage the orchestration of analytical workflows, and provide hands-on analytical support for high-stakes operational business functions, including reporting and performance management.

Responsibilities

• Client Reporting & Infrastructure: Scope and develop new client reports, while also maintaining and enhancing existing reporting pipelines. Collaborate with external clients and our internal client success team to effectively manage and triage inbound requests. Partner with Valon Technologies' data team to improve the underlying infrastructure for client reporting.

• Data Modeling & Transformation: Design, build, and maintain the production-grade data models and analytical layers using our existing stack of dbt Cloud and Airflow to ensure reliability and structure at scale.

• Data Governance & Quality: Partner with engineering and product teams to define and implement data contracts and observability frameworks (e.g., Great Expectations) to guarantee data quality and auditability for a regulated environment.

• Analytical Support: Write complex SQL queries, build dashboards (in tools like Hex or Looker), and conduct ad hoc analysis to empower operational leaders and provide deep root-cause insights into business performance.

• Compliance & Reporting: Own and fulfill third-party audit, exam, and regulatory reporting requirements, managing timelines and delivering clear, defensible outputs to clients and regulators.

Ideal Background & Qualifications

• Experience: 7+ years of combined experience in data engineering, analytics engineering, or a highly technical data analytics role, ideally at a mortgage servicer or financial institution (Series B–E startup experience is a plus).

• Technical Stack: Expertise in SQL (required), strong proficiency in Python, and proven experience with core modern data stack tools like dbt and Airflow.

• Communication: Communicate effectively with external clients, clearly synthesizing their requests, establishing realistic timelines, and proactively managing expectations, including pushing back when necessary to ensure successful outcomes.

• Architecture & Quality: Deep understanding of data architecture patterns (e.g. medallion architecture) and experience implementing data quality frameworks, observability tools, or data contracts at scale.

• Analytical Tools: Experience with data visualization tools (Hex, Looker, or equivalent) and proficiency in Google Sheets/Microsoft Excel.

• Mindset: A strong product mindset, focusing on the usability, reliability, and developer experience of the data systems you build.

• Problem-Solving: Proven ability to solve complex problems independently and build repeatable processes around novel situations.

Minimum Qualifications

• Bachelor’s Degree or equivalent professional experience in Computer Science, Data Analytics, or a similar field.

Benefits

• Compensation: competitive salary and 401(k) plan

• Health & well-being: we’ll invest in your physical and mental well-being with comprehensive medical, dental, & vision benefits

• Grow together: Company-wide orientation for you to successfully onboard and other learning & development opportunities, including regular review cycles that feature 360-degree feedback

• Generous time off: 17 days paid time off, sick days, and 11 company holidays

• Baby bonding time!: 12 weeks off for both birthing and non-birthing parents - fully paid so you can focus your energy on your newest addition

Throughout the interview process, please remember that emails will only be from valon.com email addresses. We will never ask for any personally identifiable information during the interview process itself. Please reach out to talent@valon.com if you have any requests to verify the authenticity of an outreach.

Valon is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws. Valon makes hiring decisions based solely on qualifications, merit, and business needs at the time.