Job Description
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We are seeking a highly skilled Data Engineer (MLOps) to join our dynamic team working on advanced financial technology projects. 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.
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Key Responsibilities
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* Data Pipeline Development: Design, develop, and maintain scalable data pipelines using Python, Airflow, and PySpark to process large volumes of financial transaction data.
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* MLOps Infrastructure: Implement and optimize MLOps infrastructure on AWS to automate the full machine learning lifecycle from development to production.
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* Deployment Pipelines: Build and maintain deployment pipelines for ML models using SageMaker and other AWS services.
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* Collaboration: Collaborate with data scientists and business stakeholders to implement machine learning solutions for fraud detection, risk assessment, and financial forecasting.
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* Data Quality and Security: Ensure data quality, reliability, and security across all data engineering workloads.
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* Architecture Optimization: Optimize data architecture to improve performance, scalability, and cost-efficiency.
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* Monitoring and Alerting: Implement monitoring and alerting systems to ensure production ML models perform as expected.
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Qualifications and Skills
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* Experience: 3-5 years of experience in Data Engineering with a focus on MLOps in production environments.
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* Programming Skills: Strong proficiency in Python programming and data processing frameworks (PySpark).
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* Workflow Orchestration: Experience with workflow orchestration tools, particularly Airflow.
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* AWS Stack: Hands-on experience with AWS stack, especially SageMaker, Lambda, S3, and other relevant services.
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* Machine Learning Deployment: Working knowledge of machine learning model deployment and monitoring in production.
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* Data Modeling: Experience with data modeling and database systems (SQL and NoSQL).
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* Domain Knowledge: Knowledge of financial services or payment processing domain is highly desirable.
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* Containerization: Familiarity with containerization (Docker) and CI/CD pipelines.
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* Problem-Solving Skills: Excellent problem-solving skills and ability to work in a fast-paced fintech environment.
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