Note: The job is a remote job and is open to candidates in USA. Overflow is a growth-stage fintech and SaaS company focused on enabling charitable giving through cash, stock, crypto, and other payment methods. The Senior Data Engineer will establish and own the company’s data infrastructure, including BI, governance, pipelines, warehouses, data models, and OLAP architecture, while partnering with AI and cross-functional teams to support analytics and customer-facing products.
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
Skills
- • 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
Benefits
- Equity eligibility
- Medical, dental, and vision coverage for employees and dependents
- Generous paid time off and company holidays
- Paid parental leave
- 401(k) retirement plan
- Dedicated mental health and therapy stipend to support personal well-being
- Team retreats and intentional in-person gatherings throughout the year
- Flexible work model with no company-wide in-office requirement
Company Overview
Company H1B Sponsorship