Senior Data Engineer

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. Analytics at Valon The data team at Valon is a force multiplier team that takes on various mission-critical workstreams across product and functional areas. We drive visibility on KPIs/metrics at all levels, transform data, build data products to enable operations/compliance at scale, and support our stakeholders in making data-driven decisions with analyses/metrics/experimentation where appropriate. At the nexus of all this is our core data stack; and we need to ensure it is performant, reliable, and cost-effective at scale. About the Role We are looking for a senior data engineer to own all facets of data infrastructure at Valon. You will be responsible for managing/optimizing our core data infrastructure, building/maintaining custom data ingestion pipelines, optimizing/implementing complex data transformations, and partnering with the data team to architect the optimal long-term infra strategy for Valon. You will be the data team’s infrastructure quarterback, and success will mean standing up the proper tooling or processes and flexibly problem-solving to ensure the team is able to carry out its mission efficiently and seamlessly. Responsibilities Manage/optimize our core data infra to ensure performance, reliability, and cost-efficacy at scale Optimize transformation jobs for performance and cost Reduce and stabilize data ingestion latency for mission-critical use cases Build/execute periodic maintenance routines Evaluate and correct any inefficiencies in data warehouse design Handle critical infrastructure migrations Build/procure observability tooling to give visibility into uptime/lag/drift/schema changes Define and implement best practices at scale Build/maintain custom ingestion pipelines When we need to extract data from sources not supported by EL vendors When we need high-performance/low-latency solutions Articulate and align the team on long-term infra strategy based on company needs How will our infra needs change at 10x business volume? At 100x? Partner with the data team to drive technical excellence and act as a force multiplier Take on higher complexity non-infra data/analytics projects, such as transformations, data products, controls, and analyses from time to time Ideal Background Experience: 4+ years of data engineering experience successfully creating/optimizing/scaling data stacks and supporting data teams, at least 2 years in an early- to mid-stage startup dbt: Deep knowledge and experience deploying and optimizing dbt or comparable tooling Data Management Systems: experience managing multiple types of data management systems (data warehouses, data marts, data lakes) Observability/Monitoring: experience building/procuring tools and processes to monitor end-to-end data stack health SQL: Mastery of SQL from both functionality and performance perspective Python: High level of comfort writing scripts in Python or a similar language Data warehouse management: Experience working with and tuning cloud data warehouses and compute environments. Experience with BigQuery/GCP a plusBI tool optimization/management: experience optimizing BI tool performance and managing permissions, Looker experience a plus Extract and Load: experience managing/tuning EL connector solutions (such as Fivetran, Stitch, etc.) and building custom ingestion pipelinesIndependence: strong prioritization skills, effort vs. impact thinking, stakeholder management Systems thinking and quantitative rigor: ability to reason about factors/interactions/root causes outcomes across the data stack, able to back up arguments/decisions with data Stakeholder empathy: deep understanding of data team workstreams and needs, ideally in the form of past experience as a data analyst/data scientist Benefits Base Compensation Band: $170,000 - $200,000 Compensation; competitive salary with a meaningful stake in the company via equity and our performance bonus program  Health & well-being; we’ll invest in your physical and mental well-being with comprehensive medical, dental, & vision benefits, One medical membership, and Talkspace to provide mental health support Food & meal allowance; in-office snacks, drinks, Tuesday dinners, and $400 monthly stipend towards your lunches or groceries  Grow together; learning & development opportunities including regular review cycles that feature 360 degree feedback Equipment; we’ll provide you with the equipment you need to be successful and a one-time $200 stipend for your initial desk setup  Generous time off; paid time off, uncapped sick days, and 11 company holidays  Baby bonding time!; 3 months off for birthing parents and 2 months off for non-birthing parents - fully paid so you can focus your energy on your newest addition 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 $170,000 — $200,000 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.