Adimplere
11 - 50 employees
💸 Finance
👥 B2C
Finance • B2C
Adimplere is a digital platform that specializes in helping individuals negotiate and settle their debts with creditors. By providing a user-friendly online portal, it allows users to view their debts, choose negotiation options that fit their financial situation, and secure discounts or favorable payment terms. The company emphasizes transparency and security in its debt negotiation process, assuring customers that their data is safe and protected. With a focus on facilitating efficient and straightforward debt management, Adimplere has helped many Brazilians clear their debts quickly and effectively.
Data Engineer
Job not on LinkedIn
🕒 April 1
🗣️🇧🇷🇵🇹 Portuguese Required
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Adimplere
11 - 50 employees
💸 Finance
👥 B2C
Finance • B2C
Adimplere is a digital platform that specializes in helping individuals negotiate and settle their debts with creditors. By providing a user-friendly online portal, it allows users to view their debts, choose negotiation options that fit their financial situation, and secure discounts or favorable payment terms. The company emphasizes transparency and security in its debt negotiation process, assuring customers that their data is safe and protected. With a focus on facilitating efficient and straightforward debt management, Adimplere has helped many Brazilians clear their debts quickly and effectively.
📋 Description
• Develop and improve services to load, transform and consume data, using cutting-edge technologies and the best tools available in the market; • Collaborate with data science and operations PMs to maintain a deep understanding of their business needs and support projects that rely on data infrastructure; • Continuously pursue improvements in scalability, resource efficiency, latency, and flexibility for our data services;
🎯 Requirements
• Strong knowledge of data manipulation programming, particularly Python; • Experience as a software engineer on Data Warehouse / ETL projects; • Experience with data visualization tools (Tableau, Metabase, Power BI); • A product mindset, where engineering costs are evaluated against the benefits to the product; • Solid knowledge of relational and non-relational databases (PostgreSQL, MongoDB); • Experience with technologies such as Kafka, Cassandra, Airflow, and Spark
🏖️ Benefits
• Professional development • Constructive feedback culture
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