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Fintech data engineer: building robust machine learning infrastructure

Curitiba
beBee Careers
Anunciada dia 14 junho
Descrição

About the Role

We are seeking an experienced Data Engineer with strong MLOps expertise and machine learning modeling experience in the financial domain. In this role, you will be responsible for building robust data pipelines and ML infrastructure to support our payment processing systems, fraud detection algorithms, and financial analytics solutions.

Key Responsibilities

* Data Pipeline Development
o Design, develop, and maintain scalable data pipelines using Python, Airflow, and PySpark to process large volumes of financial transaction data.
* MLOps Infrastructure
o Implement and optimize MLOps infrastructure on AWS to automate the full machine learning lifecycle from development to production.
* Deployment Pipelines
o Build and maintain deployment pipelines for ML models using SageMaker and other AWS services.
* Collaboration and Communication
o Collaborate with data scientists and business stakeholders to implement machine learning solutions for fraud detection, risk assessment, and financial forecasting.
* Data Quality and Security
o Ensure data quality, reliability, and security across all data engineering workloads.
* Optimization and Monitoring
o Optimize data architecture to improve performance, scalability, and cost-efficiency.
o Implement monitoring and alerting systems to ensure production ML models perform as expected.

Requirements and Qualifications

* 3-5 years of experience in Data Engineering with a focus on MLOps in production environments.
* Strong proficiency in Python programming and data processing frameworks (PySpark).
* Experience with workflow orchestration tools, particularly Airflow.
* Hands-on experience with AWS stack, especially SageMaker, Lambda, S3, and other relevant services.
* Working knowledge of machine learning model deployment and monitoring in production.
* Experience with data modeling and database systems (SQL and NoSQL).
* Knowledge of financial services or payment processing domain is highly desirable.
* Familiarity with containerization (Docker) and CI/CD pipelines.
* Excellent problem-solving skills and ability to work in a fast-paced fintech environment.

Why This Role Matters

This role plays a critical part in delivering cutting-edge fintech solutions and driving innovation in the financial industry. As a skilled Data Engineer, you will have the opportunity to work on advanced financial technology projects and contribute to the development of robust data pipelines and ML infrastructure.

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