Data Engineer, Python

Job not on LinkedIn

November 25

🗣️🇧🇷🇵🇹 Portuguese Required

Apply Now
Logo of Teddy Open Finance

Teddy Open Finance

Fintech • SaaS • API

Teddy Open Finance is a Brazilian fintech infrastructure company providing SaaS platforms and open finance-enabled APIs that connect banks, fintechs and credit originators. The company offers modular solutions for credit origination, compliance, document management, bancarization, payment split, white-label platforms and automation, supported by AI-driven assistant SAM IA and enterprise-grade security. Teddy operates as a digital correspondent (correspondente bancário) and primarily serves banks, fintechs and financial agents to scale distribution of multiple credit products with embedded compliance and integrations to major financial institutions.

51 - 200 employees

Founded 2020

💳 Fintech

☁️ SaaS

🔌 API

📋 Description

• Data Ingestion into the Data Lake: Develop and manage data pipelines that enable ingestion of large volumes of data in real time or in batch into the Data Lake, ensuring the quality and consistency of stored data. • Database Knowledge: Strong understanding of relational (SQL) and non-relational (NoSQL) databases, including data modeling, complex queries and performance optimization. • ETL (Extract, Transform, Load): Design and implement ETL processes to transform raw data into usable information, ensuring data is clean, formatted and ready for analysis. • Tools and Technologies: • o Apache Airflow: Workflow automation and orchestration of data processes to ensure tasks run efficiently and in the correct sequence. • o Git: Version control for code, ensuring all changes to scripts and data pipelines are tracked and team collaboration is organized and secure. • o AWS (Amazon Web Services): Use of cloud services for data storage, processing and analysis, including S3, Redshift, Lambda and other relevant services. • Programming in Python: Advanced use of Python for developing automation scripts, data manipulation, API integration and building complex data pipelines. Python is often used together with data libraries such as Pandas, PySpark, among others.

🎯 Requirements

• Strong knowledge of SQL and NoSQL. • Hands-on experience with ETL and Data Lakes. • Proficiency in Python and data-related libraries. • Familiarity with orchestration and workflow automation tools, especially Airflow. • Ability to work with version control systems such as Git. • Experience with cloud services, particularly AWS.

🏖️ Benefits

• Dental care • Payroll-deductible loan • Career development plan • Life insurance • Food allowance • Health insurance • Meal allowance • Personal guidance program - C4 Life • Day Off

Apply Now

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