Data Engineer - Data & Analytics

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.

Nice-to-Haves

• Exposure to product analytics tools like Segment, Amplitude, or Mixpanel.
• Experience in enterprise B2B SaaS or high-growth startup environments.