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We are looking for a Senior Data Engineer to join the manufacturing AI team and help us shape our machine learning solutions, data feed forward procedures, production accessibility, supporting supervised and un-supervised solution in production, quality control methodologies and anomaly detection across the manufacturing process. As a Data Engineer, you will play a meaningful role in bridging the gap between machine learning and software engineering. Your primary responsibility will be to develop, deploy, and maintain the infrastructure, data pipelines and workflows required for the end-to-end machine learning lifecycle. If you are genuinely passionate about data engineering platforms, methodologies and possesses excellent problem-solving, we'd love to hear from you!
What you’ll be doing:
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Collaborate with multi-functional teams, including data scientists, data engineers, and DevOps, to craft, implement and maintain scalable data pipelines, infrastructure and workflows.
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develop and support data models, schemas, and database structures that provide blazing-fast analytics performance. Constantly optimize data workflows to ensure seamless real-time and batch data processing.
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Implement data quality checks and monitoring mechanisms to ensure data integrity and accuracy at every stage. detect and resolve bottlenecks swiftly to maintain a highly available and reliable data ecosystem.
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Automate and streamline the ML workflow, including data ingestion, feature engineering, model training, and model evaluation, using industry's gold standard methodologies, frameworks, and tools.
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Build and maintain scalable data pipelines, ensuring efficient data storage, retrieval, and transformation for ML use cases.
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Stay ahead of the curve in data engineering technologies and trends. Introduce new tools, techniques, and best practices to enhance our data infrastructure, empowering data scientists and analysts alike.
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Foster a culture of learning and knowledge-sharing within the team. Guide and mentor junior data engineers, applying your expertise to uplift the entire department.
What we need to see:
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Bachelor’s or master’s degree in computer science, Engineering, or a related field.
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5+ years of relevant experience
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Demonstrated track record as a hands-on Data Engineer, driving the successful delivery of complex data projects. Your experience speaks volumes.
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Experience with cloud-based data platforms like AWS, Azure, or GCP. You harness the power of the cloud to unlock data's full potential.
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Strong programming skills in languages such as Python, Java, or Scala, with experience in building scalable and efficient systems.
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Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
Ways to stand out from the crowd:
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Attention to detail is unwavering. You take pride in delivering data of the highest quality, turning it into insights that power critical business decisions.
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Experience working and data engineering frameworks such as Kafka, Cloudera, Spark, Airflow or Hadoop.
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Thriving in a dynamic environment, ables to juggle multiple priorities admirably without compromising on quality or precision.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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