Data Engineer/Architect – EDGE|ML

9 hours ago

Noida, Uttar Pradesh, India Topcoder Full time ₹ 20,00,000 - ₹ 25,00,000 per year
Data Engineer/Architect - EDGE|ML

Description

EDGE|ML is an end-to-end analytics and solutions platform aiming to supply SCM, logistics, store and category managers with data, insights, and solutions to optimize their processes. EDGEJML is built on a state-of-the-art, scalable technology leveraging Google Cloud Platform managed services. The ideal candidate for the Data engineer/architect role is an experienced data pipeline/architecture builder who enjoys building from the ground up and optimizing data systems.

Your challenges
  • Augment EDGEIML offerings by enhancing, extending, optimizing, and operationalizing the analytic services
Data Architecture
  • Optimally design and work with large, complex datasets in BigQuery.
Data Engineering
  • Design, build, maintain, productionize, and operate data pipelines in GCP using Python, SQL, and Google managed services.
  • Deploy machine learning models.
  • Collaborate closely with business stakeholders, data analysts/scientists, software engineers, and platform operations staff.
You should bring in:

Data architecture
  • 5+ years of experience in Data Warehousing, Business Intelligence, Big Data.
  • Advanced working SQL knowledge and experience (CTE, window functions) working with relational databases, as well as working familiarity with a variety of databases.
  • Extensive knowledge of data modelling approaches and best practices. Experience in implementation of a data mesh architecture in Google Cloud is a strong plus.
  • Extensive knowledge of techniques for query optimization in BigQuery.
Data Engineering
  • 5+ years of experience in a Data Engineering role
  • Extensive experience building, optimizing, and productionizing 'big data' data pipelines, in Google Cloud Platform.
  • Experience designing and deploying high performance systems with reliable monitoring and logging practices.
  • Experience with source control systems (GitHub) and continuous integration & deployment tools e.g. Jenkins
  • Experience using application containerization technologies (Docker, Kubernetes), orchestration and scheduling (e.g. Google Composer, Apache Airflow)
  • Experience with machine learning using packages such as xgboost, sklearn, TensorFlow (building, deploying, monitoring)
  • Experience building data pipelines for Gen Al products

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