Lead Data Engineer

R-036717
Bangalore

Key Deliverables/Responsibilities

  • Work closely with the Product Owners and stake holders to design the Technical Architecture for data platform to meet the requirements of the proposed solution.
  • Work with the leadership to set the standards for software engineering practices within the machine learning engineering team and support across other disciplines
  • Play an active role in leading team meetings and workshops with clients.
  • Choose and use the right analytical libraries, programming languages, and frameworks for each task.
  • Help the Data Engineering team produce high-quality code that allows us to put solutions into production
  • Create and own the technical product backlogs for products, help the team to close the backlogs in right time.
  • Refactor code into reusable libraries, APIs, and tools.
  • Help us to shape the next generation of our products.

Experience Required

Essential:

  • 5-10 years of experience in delivering Advance Analytics solution Data Warehousing, Big Data or Cloud
  • Graduate degree educated in computer science or a relevant subject.
  • Strong foundation in software engineering principles and an architectural mindset.
  • Knowledge of Big Data technologies, such as Spark, Hadoop/MapReduce.
  • Strong coding skills in Java and Python.
  • Experience in architecting software solution on public cloud.
  • Experience in authoring or reviewing system design documents for enterprise solutions.
  • Deep knowledge of testing frameworks and libraries.
  • Working knowledge of the pros, cons and usages of various ML/DL applications (such as Keras, Tensorflow, Python scikit learn and R)
  • Experience of working in Agile delivery
  • Good knowledge of database management languages e.g. SQL, PostgreSQL.

Desirable:

  • Certified as  Cloud Architect from a reputed public cloud.
  • Contribution to industry/open source communities.
  • Knowledge and practical experience of cloud based ML/DL offerings (such as Google GCP, AWS, and Azure) would be advantageous
  • Understanding of infrastructure (including hosting, container based deployments and storage architectures) would be advantageous

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