We are seeking a highly skilled Data Engineer with strong MLOps expertise and machine learning modeling experience in the financial domain.
As part of our commitment to innovation, we aim to build robust data pipelines and ML infrastructure to support payment processing systems, fraud detection algorithms, and financial analytics solutions.
In this role, you will be responsible for designing, developing, and maintaining scalable data pipelines using Python, Airflow, and PySpark to process large volumes of financial transaction data.
Key Responsibilities:
* Design and develop scalable data pipelines 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 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.
Required Skills 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).
* Familiarity with containerization (Docker) and CI/CD pipelines.
Benefits and Opportunities:
This role offers the opportunity to work with state-of-the-art machine learning and cloud infrastructure in a fast-paced, growth-oriented environment.
We value collaboration, continuous learning, and innovative thinking, and offer opportunities for professional growth and development.