Quantiphi
Quantiphi
Quantiphi एक एआई-प्रथम डिजिटल इंजीनियरिंग कंपनी है, जो संगठनों को जटिल कारोबारी चुनौतियों से निपटने के लिए कृत्रिम बुद्धिमत्ता, डेटा और क्लाउड तकनीकों का उपयोग करने में मदद करती है। 2013 में स्थापित यह कंपनी परामर्श और इंजीनियरिंग विशेषज्ञता को मिलाकर बड़े पैमाने पर उपयोग किए जा सकने वाले एआई एप्लिकेशन बनाती है, डेटा विश्लेषण क्षमताएं विकसित करती है, क्लाउड अवसंरचना का आधुनिकीकरण करती है और कस्टम समाधान लागू करती है। इसका कार्य स्वास्थ्य सेवा, वित्त, शिक्षा, खुदरा और लॉजिस्टिक्स जैसे क्षेत्रों के संगठनों को सहायता देता है। इसके तकनीकी साझेदारों में AWS, Google Cloud और NVIDIA शामिल हैं। Quantiphi की टीमें उन्नत तकनीक को उद्यम रूपांतरण के लिए व्यावहारिक समाधानों में बदलने पर ध्यान केंद्रित करती हैं।

Senior Data Engineer, Onsite in India

Senior Data Engineer responsible for Azure pipelines, hybrid cloud architectures, and distributed machine learning workflows. Contribute to large-scale data modernization at Quantiphi.

विवरण

  • Help plan and implement data flows, including sizing and configuration
  • Support Solution Architects in transforming and modernizing Azure-based data solutions
  • Develop production-ready code for distributed machine learning workflows
  • Design and implement Azure data pipelines and streaming data flows
  • Build hybrid data solutions that integrate on-premises and cloud services
  • Investigate complex distributed-systems issues and deliver scalable solutions
  • Create tools for ingesting and processing terabytes of data each day
  • Collaborate with product owners, analysts, architects, platform engineers, and cloud vendors
  • Prepare detailed designs, technical specifications, and test plans
  • Own development tasks, production releases, and post-production support
  • Assist with unit, system integration, and user acceptance testing
  • Coordinate testing and migration activities with business and support teams

आवश्यकताएँ

  • 4–7 years of professional experience
  • Currently serving a notice period of 0–15 days
  • Strong hands-on experience with Spark and PySpark
  • Advanced SQL skills, including query performance optimization
  • Strong practical experience with Python, Java, or Scala
  • Experience working with Azure, AWS, or Google Cloud Platform
  • Experience with Azure Data Factory is advantageous
  • Databricks experience is desirable
  • Experience with Snowflake or Synapse data warehouses
  • Ability to design dimensional models for data warehouses and marts
  • Knowledge of version control and build automation tools, including Azure DevOps and/or MLOps
  • Understanding of operating system internals, file systems, disk and storage technologies, and storage protocols

लाभ

  • A culture centered on transparency, diversity, integrity, learning, and growth
  • An environment that supports innovation and both professional and personal development

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