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    Data Engineer - Delhi, India - Resources valley

    Resources valley
    Resources valley Delhi, India

    1 day ago

    Default job background
    permanent Technology / Internet
    Description

    Job Description :
    Ownership of Data Engineering solution development, including ingestion, transformation, loading, modelling, curation, profiling, migration, and validation of data, also maintaining security, access control, compliance, and SLAs

    • Design and create data models and data pipelines and provide highquality, performant, and reliable data solutions to the stakeholders
    • Executes project deliverables, timelines, and dependencies for team members and stakeholders following an agile/SDLC to reduce time to market
    • Establish processes to enable proactive planning and expansion of infrastructure based on usage and adoption
    • Recommend technical solutions based on business requirements and prioritization
    • Implement success metrics for adoption and for tracking the business value of investments at the enterprise level
    • Create/propose solutions for enterprisewide deployment with considerations around scale and costs
    • Address issues/risks/dependencies in solution recommendations.
    Acts as a technical lead to other information engineers (including offshore and contract resources). Help the team make critical technical decisions, unblock them, and guide them on execution.

    • Bachelor's Degree in Computer Science or equivalent work experience
    • 5+ years of professional development experience working in enterprisescale data modelling, integration/migration & modern cloud data warehousing.
    • You must know modern data stack tools like Snowflake, SnowPark, DBT, SQL, Python, Airflow, AWS Glue, Fivetran, Redshift, Atlan, etc.
    • 5+ years of data engineering experience is required
    • Must know one or more Data visualization tools such as Tableau, Looker, Qlik Sense, PowerBI, or other
    • Experience working in the agile development environment
    • 5+ years of designing, implementing, and building data engineering solutions that deliver measurable quality under the SLA
    )
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