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.
About This Role
This remote position offers the opportunity to work with state-of-the-art machine learning and cloud infrastructure in a fast-paced, growth-oriented environment.
* Main Responsibilities:
* 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.
* Evaluate 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.
About Your Qualifications
* We are looking for candidates with 3-5 years of experience in Data Engineering with a focus on MLOps in production environments.
* You should have strong proficiency in Python programming and data processing frameworks (PySpark).
* Experience with workflow orchestration tools, particularly Airflow, is highly desirable.
* A hands-on understanding of AWS stack, especially SageMaker, Lambda, S3, and other relevant services, is necessary.
* A working knowledge of machine learning model deployment and monitoring in production is required.
* Data modeling and database systems (SQL and NoSQL) are also essential skills.
* A familiarity with containerization (Docker) and CI/CD pipelines would be beneficial.
* You must possess excellent problem-solving skills and the ability to work in a fast-paced fintech environment.
Becoming Part of Our Team
If you're a skilled Data Engineer looking to contribute your expertise to a cutting-edge project, we encourage you to apply.