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    Senior Data Engineer - Bangalore/Hyderabad/Pune, India - LAGNUS PRIVATE LIMITED

    LAGNUS PRIVATE LIMITED
    LAGNUS PRIVATE LIMITED Bangalore/Hyderabad/Pune, India

    Found in: Talent IN 2A C2 - 3 days ago

    Default job background
    permanent Technology / Internet
    Description

    About the job :

    ROLE : Snowflake and Matillion Data Engineer

    JD :

    Experience : 4 to 6 Years

    Overview :


    - Design, implement, and optimize data pipelines and workflows using Snowflake and Matillion to support our data integration, transformation, and analytics initiatives.

    - Collaborate with cross-functional teams to gather requirements, define data models, and develop solutions that meet business needs.

    - Develop and maintain ETL processes to extract, transform, and load data from various sources into Snowflake data warehouse for analysis and reporting purposes.

    - Monitor pipeline performance, troubleshoot issues, and implement enhancements to ensure data accuracy, reliability, and efficiency.

    - Stay updated on emerging technologies and best practices in data engineering, Snowflake, and Matillion to drive continuous improvement and innovation.

    1) Work Mode : WFO, Pune.

    2) Joining Time : Immediate only

    3) Shifts if any : General

    4) Interview Process : L1 and L2

    5) Hiring Mode : C2H

    Responsibilities :

    Design, develop, and maintain scalable data pipelines and ETL processes to ingest, transform, and store large volumes of data from diverse sources.

    Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and translate them into technical solutions.

    Implement data models, schemas, and structures to support efficient data storage, retrieval, and analysis.

    Optimize data processing and query performance using distributed computing frameworks such as Apache Spark, Hadoop, or similar technologies.

    Develop and maintain data integration solutions using tools like Apache Kafka, Apache NiFi, or cloud-based services (e.g., AWS Kinesis, Google Pub/Sub).

    Ensure data quality and integrity by implementing data validation, cleansing, and reconciliation processes.

    Monitor and troubleshoot data pipeline issues, performance bottlenecks, and system failures to ensure high availability and reliability.

    Implement data security and compliance measures to protect sensitive data and ensure regulatory compliance.

    Mentor and provide guidance to junior members of the data engineering team,and promote best practices for data engineering and software development.

    )
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