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Who we are: Sardine is the leading agentic risk platform for fighting financial crime. Our integrated solution unifies data across risk teams to help organizations stop fraud in real time, prevent AI-driven attacks, and automate fraud and AML operations. Sardine’s platform is strengthened by one of the fastest-growing fraud consortiums in the market, spanning more than 6 billion profiled devices, 800 million consumers, and 3 million businesses worldwide. Leading companies including FIS, GoDaddy, Intuit, Edward Jones, ZoomInfo, and Checkout.com rely on Sardine to secure and grow trust in their products. Our culture: - We have hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo. However, we maintain a remote-first work culture. #WorkFromAnywhere - We hire talented, self-motivated individuals with extreme ownership and high growth orientation. - We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule. About the role We are looking for a Data Engineer to lead the development of Sardine’s internal data platform, connecting GTM, product analytics, and business data sources into a single, scalable system that drives decision-making across the company. This is a high-impact, highly technical role sitting at the intersection of data engineering and analytics engineering. You will own the core data foundation that enables our executive team, revenue operations, finance, product, and customer-facing teams to make faster, better-informed decisions. You will also own critical backend infrastructure including billing data, warehouse security, and ETL pipelines that pull from both internal and external systems. Data accessibility and consistency are central to Sardine’s next stage of growth, and this role is at the center of that mission. What you’ll be doing - Build and own Sardine’s internal data infrastructure, integrating CRM, marketing, product, finance, and operational systems into a cohesive, well-modeled data warehouse. - Own the data warehouse partitioning strategy, access controls, and security architecture in close partnership with the Security and Infrastructure teams to meet compliance and performance requirements. - Take full ownership of billing data infrastructure, including backend warehouse tables, data models, and ongoing maintenance. - Design, implement, and own ETL/ELT pipelines to pull and merge data from multiple internal and external systems, ensuring clean, reliable, and scalable data flows across the organization. - Partner with data science, engineering, revenue operations, and executive stakeholders to define and track KPIs, ensuring business decisions are grounded in data. - Serve as the connective tissue between Revenue Operations, Business Operations, and Product/Eng, translating complex requirements into elegant data solutions. - Champion data quality and governance, ensuring insights are consistent, trustworthy, and well-documented. - Build dashboards and analytics that provide key insights for executive leadership, GTM, product, and finance teams. - Analyze data to identify the best ways to deliver value to clients and inform product decisions. What you’ll need - 5+ years of experience in data engineering, analytics engineering ideally supporting GTM or business functions. - Expertise in Python with strong SQL skills and experience building with a modern data stack (BigQuery, dbt, Fivetran, Airflow). - Proven ability to manage data integrations across platforms such as Salesforce, HubSpot, BigQuery/Snowflake, Amplitude, Sigma, Clay, and similar tools. - Hands-on experience with AWS or GCP, containerization (Docker, Kubernetes), and CI/CD pipelines. - Experience building and maintaining scalable data visualization solutions (Sigma, Looker, Tableau). - Familiarity with cred