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.

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.

Data Engineer, Data & Analytics

Key skills