Financial Data Engineer Position
We are seeking a skilled Financial Data Engineer to join our team. This individual will be responsible for designing, developing, and maintaining scalable data pipelines using Python, Airflow, and PySpark to process large volumes of financial transaction data.
The successful candidate will have experience with workflow orchestration tools, particularly Airflow, and hands-on experience with AWS stack, especially SageMaker, Lambda, S3, and other relevant services.
In addition to technical skills, the ideal candidate will possess excellent problem-solving skills and ability to work in a fast-paced fintech environment.
We are looking for a highly motivated and experienced professional who can collaborate with data scientists and business stakeholders to implement machine learning solutions for fraud detection, risk assessment, and financial forecasting.
The Financial Data Engineer will be responsible for building robust data pipelines and ML infrastructure to support payment processing systems, fraud detection algorithms, and financial analytics solutions.
The key responsibilities include:
* Designing, developing, and maintaining scalable data pipelines using Python, Airflow, and PySpark.
* Implementing and optimizing MLOps infrastructure on AWS.
* Building and maintaining deployment pipelines for ML models using SageMaker and other AWS services.
* Collaborating with data scientists and business stakeholders to implement machine learning solutions.
* Ensuring data quality, reliability, and security across all data engineering workloads.
The ideal candidate will have 3-5 years of experience in Data Engineering with a focus on MLOps in production environments.
We offer a competitive salary and benefits package, as well as opportunities for growth and development in a dynamic and innovative company.
We are an equal opportunities employer and welcome applications from diverse candidates.
Please submit your application, including your resume and cover letter, to us.