Lead Data Engineer

5 years

8 - 9 Lacs

Posted:3 hours ago| Platform: GlassDoor logo

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Work Mode

On-site

Job Type

Part Time

Job Description

JOB DESCRIPTION


Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference.

As a Lead Data Engineer at JPMorgan Chase within the Consumer & Community Banking, you play a crucial role in an agile team dedicated to improving, developing, and providing data collection, storage, access, and analytics solutions that are secure, stable, and scalable.

Job responsibilities

  • Design and implement ‘data models’ to support business requirements and analytics.
  • Develop and maintain MLOps pipelines for automating the deployment and monitoring of machine learning models.
  • Collaborate with data architects, data scientists, data engineers, and product owner to understand data needs and translate them into data models.
  • Ensure data models and machine learning models are optimized for performance and scalability.
  • Conduct data analysis and profiling to understand data quality and integrity.
  • Develop and maintain CI/CD pipelines for machine learning projects.
  • Document data models, metadata, and machine learning processes for reference and compliance purposes.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands on experience in Data Modeling and MLOps
  • Strong idea on Data warehousing, Data lakes and their Architecture patterns
  • Proficiency in data modeling tools such as ER/Studio, ERwin, or similar.
  • Experience in deploying and managing machine learning models in production.
  • Proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
  • Strong understanding of DevOps practices and tools.
  • Excellent analytical, problem-solving, and communication skills.
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