Last-mile delivery platform built on event streaming and analytics infrastructure
Quero Delivery operates a delivery logistics platform with a polyglot backend (MongoDB, MySQL, PostgreSQL) and a data stack built around Kafka, Python (Pandas, NumPy, scikit-learn), and BI tools (Tableau, Power BI, Looker, Metabase). Active projects center on data pipeline maturity—ETL from MongoDB to MySQL, data quality implementation, and ML model monitoring—while pain points signal operational friction: maintaining partner relationships, scaling the data team, and controlling inference latency and cost. The 51–200 employee org is junior-to-mid weighted and hiring primarily in data (4 open roles) and sales (3), suggesting a shift toward data-driven operations.
Quero Delivery is a Brazilian last-mile delivery platform founded in 2018 and headquartered in Lagarto, Sergipe. The product connects customers with restaurant and retail partners for same-day delivery. The company operates a classic logistics stack—order routing, logistics coordination, and partner relationship management—layered with an emerging analytics function. Current operational focus spans sales strategy and target execution alongside foundational data work: pipeline reliability, data quality assurance, and production ML monitoring. Hiring velocity is accelerating, with most new roles concentrated in data engineering and sales.
MongoDB, MySQL, PostgreSQL for data storage; Python (Pandas, NumPy, scikit-learn) for analytics; Kafka for event streaming; Tableau, Power BI, Looker, Metabase for BI; AWS for infrastructure; GitHub for version control.
ETL pipeline development (MongoDB to MySQL migration), data quality implementation, ML model drift monitoring and cost optimization, sales strategy refinement, and sales forecasting—indicating a shift from operations-first to data-driven logistics.
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