dv01

Analytics Engineer

• Be at the heart of dv01. You’ll operate as the bridge between the engineering and analyst teams, contributing to a variety of integral processes that drive dv01 on a daily basis. Every new dataset that gets integrated within dv01 will have your fingerprints all over it.
• Be an owner of dv01's most valuable asset. You'll own managing and scaling the business logic in our data pipeline, encapsulating all the knowledge we've accumulated across hundreds of datasets. The output from the pipeline powers all of dv01's customer offerings and is critical to the success of our business.
• Work directly with internal and external stakeholders. You’ll work with our team of analyst experts as well as directly connecting with customers to understand the complexities of the data dv01 manages.
• Work with state-of-the-art technology. You'll work with popular, modern, and exciting open source technologies like dbt, Airflow and Apache Spark. Everything we do is cloud-native on Google Cloud Platform, utilizing tools including BigQuery, Cloud Run and Dataproc. The skills you develop here will serve you well beyond dv01.

Data Analytics Engineer I

Technical Project Manager

• Manage all lifecycle stages for a project post ideation with responsibility for ensuring that deliverables are understood and releases are delivered on time. For projects, you will define and track success metrics that tie back to business outcomes, not just delivery dates
• Partner with engineering teams to help translate technical requirements and system dependencies into actionable project plans, ensuring workstreams stay aligned and progress is clearly communicated across teams.
• Leverage AI-powered tools to improve project coordination, including synthesizing updates, generating documentation, and helping surface risks or dependencies across technical workstreams to support more efficient execution.
• Connect the dots of complex workflows in a fast-paced environment. You will be responsible for engaging key stakeholders across business, technology, and product while working closely with software engineers to build consensus, resolve conflicts, and ensure smooth execution.
• Ensure the quality of project deliverables. You will work with all stakeholders to establish quality standards and monitor adherence to quality in day-to-day execution.

Technical Project Manager I

Backend Engineer

• Bring transparency to the financial markets: You will bring transparency to consumer lending, mortgages, and other asset classes, by enabling our customers at banks, hedge funds, and credit originators via our SaaS offering including our Cashflows API product to quickly extract insights from large private and public datasets.
• Develop using a modern, open source stack: You will develop on top of a software stack that includes Kotlin + Spring Boot with some legacy apps built on Scala + ZIO and Python + FastAPI. We continuously evaluate and adopt new open source technologies to solve customer needs, so the skills you develop here will serve you well beyond dv01.
• Interact with a diverse team: You will collaborate closely with other teams at dv01 to create great products. This includes working closely with the product team to understand the customer story, design team to understand the motivation behind the UI/UX, the data engineering team to understand the most efficient way to query that data, and finally front-end engineers to fully build out the product.
• Gain knowledge of the financial industry: You will have an exclusive view into the system that enables Americans to afford houses, cars, and college. You will learn about the participants, terminology, and mathematics behind this sector of the financial markets.

Senior Backend Engineer

Platform Engineer

• Build and operate an AI infrastructure platform: You will design, build, and operate cloud-native infrastructure and platform tooling that accelerates AI development across the company. This includes enabling teams to develop, deploy, and operate AI-powered services safely and efficiently in production environments.
• Own the DevOps and infrastructure side of MLOps and Agentic Systems: You will focus on the operational foundations of AI systems, including CI/CD for AI workloads, scalable inference infrastructure, observability, cost management, and reliability. You will establish repeatable patterns and shared services that reduce friction for teams building AI-enabled applications.
• Enable AI services, agents, and runtime platforms: You will build and maintain infrastructure to support AI services such as LLM-backed APIs, Model Context Protocol (MCP) servers, and agentic systems used by production applications. You will enable secure tool access, runtime orchestration, and isolation boundaries for AI-driven workloads.
• Integrate MLOps capabilities into platform operations: You will apply MLOps concepts to improve platform operations, including using AI-driven approaches for monitoring, alerting, anomaly detection, and incident response across AI and non-AI systems. You will help evolve how the platform observes and operates complex AI-enabled systems at scale.
• Establish governance, security, and operational guardrails: You will help define and implement infrastructure-level governance for AI systems, including access controls, deployment policies, auditability, and secure-by-default patterns. You will partner with security and compliance teams to ensure AI infrastructure aligns with organizational risk and regulatory requirements.
• Provide technical leadership and enablement: You will act as a technical leader, influencing platform architecture and best practices across teams. You will mentor engineers and work closely with product, data, and application teams to align AI platform capabilities with business goals.

Data Analytics Engineer I

Technical Project Manager I

Senior Backend Engineer

MLOps Platform Engineer