Payment platform with built-in loyalty and customer retention analytics
Frekuent operates a payment and loyalty platform aimed at converting repeat purchases into customer lifetime value. The tech stack reveals a data-first operating model: SQL + Python + dbt + BigQuery + Snowflake form the backbone, with Fivetran and Airflow orchestrating pipelines, while Looker and Tableau surface insights to the business. Active projects in A/B testing, revenue operations, and onboarding workflow optimization, paired with acute pain points around churn, upsell identification, and data quality across billing/CRM systems, suggest the platform is scaling beyond transactional payments into retention analytics — a shift requiring deeper operational data integration.
Frekuent is a Barcelona-based payment solutions company founded in 2016, serving mid-market businesses that need to combine payment processing with customer loyalty and retention mechanics. The product lets merchants embed rewards and engagement features directly into the payment experience, supported by real-time analytics on customer behavior and lifetime value. The organization leans heavily into sales (9 roles) and marketing (4 roles), with a much smaller engineering team (3 roles), indicating a sales-driven go-to-market model. Current hiring is concentrated in Spain and skewing toward mid-to-senior talent.
Core: SQL, Python, dbt, BigQuery, and Snowflake for data architecture. Orchestration via Apache Airflow and Fivetran. BI and dashboarding via Looker and Tableau. Operations tooling: HubSpot, Salesforce, Zendesk, Google Workspace, Azure AD.
Active projects include data warehouse and modeling, A/B testing and experimentation, dashboard and KPI tracking, data pipeline development, revenue operations systems implementation, CRM data cleanup, and onboarding workflow optimization.
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