Data Engineer

Overflow is a Series C, growth-stage technology company on a mission to inspire the world to give. They are seeking a dedicated Data Engineer to establish a robust data and analytics ecosystem, taking ownership of data infrastructure and ensuring reliable access to metrics for various teams.

Responsibilities:

• Architect, build, and own Overflow's core data infrastructure from the ground up — pipelines, warehouses, data models, and orchestration
• Design and implement scalable ETL/ELT pipelines that collect, transform, and deliver clean, reliable data across Overflow's platform and business functions
• Build and maintain a unified data layer that integrates data across Engineering, Product, Finance, Revenue, Success, and Operations
• Design well-structured, intuitive data models that empower self-service analytics across the company and power OLAP views in customer facing applications
• Build and maintain dashboards and reporting infrastructure that give leadership real-time visibility into key business metrics — total giving volume, client sentiment, payment revenue
• Partner with the Head of AI to design storage schemas and organization strategies for semi-structured and unstructured data, providing the clean structures required to power advanced MLOps, RAG pipelines, and agent memory
• Implement Databricks Unity Catalog to establish strict data governance, documentation standards, access controls, and role-based visibility across the organization
• Build for reliability by implementing data quality monitoring, alerting, and validation frameworks to ensure data accuracy and trustworthiness
• Collaborate closely with Engineering, Product, Finance, Payment Ops, Support, and RevOps to understand data needs and deliver scalable solutions
• Act as the internal expert and advocate for data — educating teams on best practices and helping them ask better questions of the data
• Contribute to the product roadmap by surfacing data-driven insights about customer behavior, platform performance, and market opportunity

Requirements:

• Core Experience: 5+ years of Data Engineering experience, ideally acting as the first or lead Data Engineer at a fast-growing tech, fintech, or SaaS company
• Data Modeling: Proven ability to design efficient OLAP schemas for complex financial transactions and business metrics
• Cloud & Pipeline Skills: Strong proficiency with AWS data services and building reliable Change Data Capture pipelines
• Database Knowledge: Strong familiarity with NoSQL databases and a deep understanding of relational SQL databases
• Cross-Functional Communication: The ability to translate complex business requirements from Finance and Sales into technical data models, and the collaborative skills to work seamlessly with MLOps, Business Operations, and Software Engineering teams
• Databricks Expertise: Hands-on experience working specifically within a Databricks environment, including leveraging Unity Catalog for governance, Delta Lake, and native Databricks SQL/BI tools
• Fintech Knowledge: An understanding of the fintech ecosystem, particularly handling transactional data, ledgering, and reconciliation and working in SOC 2 aligned environments
• Startup DNA: Previous experience as a founding data engineer or early data team member at a high-growth startup. You thrive in ambiguity and love the 0-to-1 journey of building infrastructure from scratch