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Financial data engineer (mlops)

Valença do Piauí
beBee Careers
Anunciada dia 14 junho
Descrição

Skill in demand: Financial data engineer with MLOps expertise required.

At a leading fintech company, we are looking for a highly skilled Data Engineer (MLOps) to join our dynamic team working on advanced financial technology projects. This remote role offers the opportunity to work with state-of-the-art machine learning and cloud infrastructure in a fast-paced, growth-oriented environment.

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.

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

Key qualifications include 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 (Airflow), and hands-on experience with AWS stack (SageMaker, Lambda, S3).


Required Skills and Qualifications

* Expertise in Python, PySpark, and Airflow
* Hands-on experience with AWS (SageMaker, Lambda, S3)
* Machine learning model deployment and monitoring
* Data modeling and database systems (SQL and NoSQL)
* Containerization (Docker) and CI/CD pipelines


Benefits and Perks

This is a remote role offering the opportunity to work in a fast-paced fintech environment with state-of-the-art machine learning and cloud infrastructure.

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