Advanced Data Engineering Role
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This position involves the development and maintenance of scalable data pipelines using Python, Airflow, and PySpark to process large volumes of financial transaction data. The successful candidate will have strong proficiency in Python programming and data processing frameworks (PySpark), as well as experience with workflow orchestration tools, particularly Airflow.
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The ideal candidate will also have hands-on experience with AWS stack, especially SageMaker, Lambda, S3, and other relevant services. Additionally, they should have a working knowledge of machine learning model deployment and monitoring in production, as well as experience with data modeling and database systems (SQL and NoSQL).
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A key aspect of this role is ensuring data quality, reliability, and security across all data engineering workloads. The candidate will also be responsible for optimizing data architecture to improve performance, scalability, and cost-efficiency.
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Responsibilities include:
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* Designing, developing, and maintaining scalable data pipelines
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* Implementing and optimizing MLOps infrastructure on AWS
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* Building and maintaining deployment pipelines for ML models
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* Collaborating with data scientists and business stakeholders to implement machine learning solutions
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* Ensuring data quality, reliability, and security
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* Optimizing data architecture
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Qualifications and skills required for this role include 3-5 years of experience in Data Engineering with a focus on MLOps in production environments. Strong problem-solving skills and ability to work in a fast-paced fintech environment are also essential.
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This is an excellent opportunity for a skilled Data Engineer to join a dynamic team working on advanced financial technology projects. The remote nature of the role offers flexibility and the chance to work with state-of-the-art machine learning and cloud infrastructure.
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Key Qualifications
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We are seeking an experienced Data Engineer with strong MLOps expertise and machine learning modeling experience in the financial domain. If you have a passion for data engineering and a desire to work in a cutting-edge fintech environment, this could be the perfect opportunity for you.