Financial Data Engineer Role
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We are seeking a skilled Data Engineer with expertise in MLOps to join our team working on advanced financial technology projects.
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This role offers the opportunity to work with state-of-the-art machine learning and cloud infrastructure in a fast-paced, growth-oriented environment.
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Key Responsibilities:
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* Design, develop, and maintain scalable data pipelines using Python, Airflow, and PySpark to process large volumes of financial transaction data.
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* Implement and optimize MLOps infrastructure on AWS to automate the full machine learning lifecycle from development to production.
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* Build and maintain deployment pipelines for ML models using SageMaker and other AWS services.
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* Collaborate with data scientists and business stakeholders to implement machine learning solutions for fraud detection, risk assessment, and financial forecasting.
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* Ensure data quality, reliability, and security across all data engineering workloads.
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* Optimize data architecture to improve performance, scalability, and cost-efficiency.
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* Implement monitoring and alerting systems to ensure production ML models perform as expected.
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Required Skills and Qualifications:
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* 3-5 years of experience in Data Engineering with a focus on MLOps in production environments.
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* Strong proficiency in Python programming and data processing frameworks (PySpark).
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* Experience with workflow orchestration tools, particularly Airflow.
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* Hands-on experience with the AWS stack, especially SageMaker, Lambda, S3, and other relevant services.
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* Working knowledge of machine learning model deployment and monitoring in production.
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* Experience with data modeling and database systems (SQL and NoSQL).
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* Knowledge of the financial services or payment processing domain is highly desirable.
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* Familiarity with containerization (Docker) and CI/CD pipelines.
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* Excellent problem-solving skills and ability to work in a fast-paced fintech environment.
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Benefits:
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* A dynamic work environment with opportunities for growth and professional development.
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* A competitive compensation package.
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* The chance to work with cutting-edge technologies and innovative projects.
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Others:
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* A high degree of autonomy and independence in your work.
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* The opportunity to collaborate with experienced professionals in the field.
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* Professional training and support to help you achieve your career goals.
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