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    Data Engineer - hyderabad, India - Aragen Life Sciences

    Aragen Life Sciences
    Aragen Life Sciences hyderabad, India

    1 month ago

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    Default job background
    Pharmaceutical / Bio-tech
    Description

    Role:
    Data Engineer


    Role Band:
    Manager

    Reporting To:
    Data Science & AI Head

    Location:
    Hyderabad

    Context
    The Data Engineer will be a part of Aragen Digital X team and will build systems that collect, manage and convert raw data into usable information which will serve as an input for further analysis by Business Analysts, Application development and Data Scientists
    Candidate would be expected to independently/with minimal supervision :
    Design and implement complex, distributed system which provides an efficient data pipeline for scalable ML analysis, and data transformation and analytics
    Architect data warehouses / data lakes etc. with big data technologies such as Spark, Python & Kafka and leveraging Maching Learning cloud platforms such as AWS
    Track data consumption patterns, performing intelligent sampling and caching, monitor schema changes and recommend opportunity areas
    Identify tooling and infrastructure capabilities to enable teams to efficiently complete and maintain data science projects
    Actively contribute to Engineering Process efficiencies such as CI/CD, Security enhancements, quality improvements, etc.
    Ensure responsible consumption of the provisioned data through governance mechanisms and compliance initiatives
    Have a good understanding of Agile, MLOps and DataOps principles
    Knowlegde about data visualization will be added advantage
    Operating Network

    Internal:
    CDO, Data Engineering Lead and Technology Tower Leads, Business Stakeholders – BU Heads, Functional Heads and their teams; IT Delivery Teams including SAP, Digital, Analytics, Infra & Security

    External:
    Digital Ecosystem partners – Academia, Start-ups, Digital Giants, Technology Solution & Service Providers, Consulting Firms, Independent Research Firms, Capability Building Partners, Industry Peers

    Contemporary Skills:
    Must have good knowledge of Agile Methodologies, Design Thinking, User Experience, Platform Business Models and Digital Technologies

    Educational Qualifications:
    M.Sc. or Ph.
    D. in Chemistry OR BE/ B. Tech from IIT or Tier I colleges
    An advanced degree (MS or higher) in computer science, statistics, applied mathematics, data management, information systems will be an added advantage
    Certification in Big Data Technologies
    Certification in Cloud Platforms AWS
    Know-how of Quantum Computing is an added advantage

    Experience Required:
    7 to 10 years of experience in the field of Data Engineering
    5 to 7 years experience in data management discipline which includes data ingestion, preparation, cleansing, provisioning, automated testing, and quality checks
    4+ years of hands-on experience in Big Data Technologies such as Data Lakes, and Data Warehouses
    Strong experience with advanced analytics tools using languages such as R, Python, Scala or others
    Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets
    Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production
    Experience in designing and building streaming data platforms in Lambda / Kappa architectures
    Key Personal Attributes

    • Strategic and Innovative Mindset
    • Executionoriented with handson experience of delivering Analyticsfocussed Initiatives
    • Business focused, Customer & Service minded
    • Strong Consultative and Management skills
    • Good Communication and Interpersonal skills to manage senior stakeholders in business and IT
    • Confident in advising, developing, and articulating solutions
    • Result oriented and with a work ethic of delivering ontime and in scope
    • Learning Agility

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