Data Engineer - Data & Analytics

Sardine is a leader in fraud prevention and AML compliance, leveraging advanced technologies to combat fraud. They are seeking a Data Engineer to develop an internal data platform that integrates various business data sources, enabling informed decision-making across the company.

Responsibilities:

• 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

Requirements:

• 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 credit or financial data and the regulatory considerations that come with handling sensitive information
• Strong communication and stakeholder management skills, with the ability to partner effectively with executives and non-technical teams
• A bias toward action and comfort working in ambiguity. You find answers rather than wait for direction
• Exposure to product analytics tools like Segment, Amplitude, or Mixpanel
• Experience in enterprise B2B SaaS or high-growth startup environments