Hello! We’re Cashea 👋, and we're on a mission to bring optimism back to Venezuelans 🇻🇪 by building innovative financial products. Since our launch in 2022, we've been dedicated to democratizing financial inclusion through cutting-edge technology. In that time, we've grown to serve over 6 million customers, developed a range of products for both consumers and merchants, and become a trusted name in Venezuela—winning both minds and hearts 💛.
About the role:
As Data Engineering Manager, you will design and develop scalable real-time and batch data pipelines to support analytical products like dashboards, recommendation engines, and automation tools. You will collaborate with data scientists and business teams to create APIs and data services that expose data and machine learning outputs. You’ll build backend infrastructure for analytics platforms using GCP services like BigQuery, Dataflow, and Pub/Sub, and work with front-end teams to support the creation of user-facing analytical tools. Additionally, you will lead the implementation of cost-effective architectures, ensure data quality and security, and mentor junior engineers while contributing to a strong engineering culture.
Overall you will...
Design and develop scalable, real-time and batch pipelines to support analytical products such as dashboards, recommendation engines, and task automation tools.
Collaborate with data scientists and business teams to create APIs and data services that expose data and machine learning outputs to internal and external consumers.
Build the backend infrastructure for advanced analytics platforms using GCP services such as BigQuery, Dataflow, and Pub/Sub or similar.
Work with front-end and full-stack developers to support the creation of user-facing analytical tools and dashboards.
Lead the implementation of scalable, cost-effective architectures for data products.
Participate in the design of data models and schemas that support analytics-driven software.
Ensure data quality, security, and compliance with regulatory requirements such as GDPR and PCI DSS.
Mentor junior engineers and contribute to building a strong engineering culture.
Qualifications
6+ years of experience in Data Architecture and/or Software Engineering, plus at least +1 years of experience as Lead, ideally in fintech, SaaS, or analytics-heavy industries.
Strong experience with GCP technologies is mandatory (BigQuery, Dataflow, Pub/Sub, Cloud Run)
Proficiency in building RESTful APIs or other data services for analytics consumption.
Expertise in ETL/ELT pipelines using tools like dbt/Dataform or Airflow.
Solid programming skills in Spark, Python or Java and SQL expertise.
Familiarity with creating infrastructure for data products and integrating with front-end or external systems.
Knowledge of governance and data security standards.
Mentor junior engineers and contribute to building a strong engineering culture.
Ability to work cross-functionally with data scientists, product managers, and business teams.
Spanish and English proficiency
