Valon

Compensation

Full Description

About the Company Valon's mission is to empower every homeowner. We believe the journey of home ownership starts when you get your keys, but lasts far beyond. We're creating a world where home ownership comes with ease, security, and financial know-how. Our growing team of engineers, operators, product enthusiasts, and experienced servicing professionals are leveraging technology to fundamentally improve the homeownership experience. Through mortgage servicing-the process of paying off one's mortgage-Valon is taking the first step in transforming the industry one homeowner, and lender, at a time. About the Role We are looking for full-stack data analysts who can take end-to-end ownership of the data and analytics needs of Valon's SaaS customers. You will be responsible for large scale migrations of varying reporting infrastructure to the Valon Data Schema and API on behalf of clients. You will interface with clients, stand up data infrastructure, migrate or build out reporting, and more. You'll work closely with client data teams, representing Valon as both the expert on Valon's Data Schema, and also mortgage servicing best practices. The right candidate is technical, analytical, and works well under pressure including high stakes and tight deadlines. At the same time, positivity, clear communication, and customer service are key. Responsibilities • Collect and document client requirements at the project level from client data analysts. • Establish new data processes, tools, and systems for clients according to plan. • Create reporting pipelines in dbt. • Write, re-write, or migrate SQL queries, reports, and dashboards to empower client operational processes. • Conduct analysis to inform client business decisions. • Document, audit, and improve client data sets to meet client data needs. • Respond to data requests from the client and their operations teams. • Meet tight project deadlines. • Dive deep into the mortgage servicing industry to understand its complicated inner workings. Additional Senior Level Responsibilities • Collect and document client requirements at the client relationship level from client executives, middle management, and data analysts. • Architect and establish new data processes, tools, and systems for clients, owning project timelines and deliverables, including accountability for milestones and deadlines. • Educate clients on data tools that increase the efficiency of their operations teams. • Ensure long term success and retention of client relationships. Ideal Background • 4+ years (6+ for Senior) of full-time work experience in data analytics, product analytics, business analytics, or business intelligence, ideally at a tech company (mortgage servicing experience a plus). • Experience in a customer facing role. • Expert in SQL required (Python skills a plus). • Experience with dbt. • Experience using data visualization tools, especially Hex, Looker, PowerBI, Tableau or equivalent BI tools. • Experience working with data engineering teams and building out data infrastructure. • Experience applying data and analytics concepts to business problems. This Base Compensation pay range applies to our New York City located staff and may differ according to location. New York Base Compensation Pay Range $105,000-$218,500 USD Throughout the interview process, please remember that emails will only be from valon.com emails. We won't ever be asking 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.