Job Title: Senior Financial Data Architect
Key Responsibilities:
* Data Engineering and MLOps Expertise: We are seeking an experienced data engineer with strong MLOps expertise and machine learning modeling experience in the financial domain.
* Design and Development: 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.
* Scalability and Performance: You will design, develop, and maintain scalable data pipelines using Python, Airflow, and PySpark to process large volumes of financial transaction data.
Role Overview: As a senior data architect, you will collaborate with data scientists and business stakeholders to implement machine learning solutions for fraud detection, risk assessment, and financial forecasting. Your expertise will ensure data quality, reliability, and security across all data engineering workloads.
Qualifications & Skills: To succeed in this role, you should have 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) is essential. Experience with workflow orchestration tools, particularly Airflow, and hands-on experience with AWS stack, especially SageMaker, Lambda, S3, and other relevant services are also required.
About the Role: 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. If you are passionate about data engineering and MLOps, and have excellent problem-solving skills, we encourage you to apply for this exciting opportunity.