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    SLB - MDM Developer - Data Warehousing - Coimbatore, India - Schlumpbergers Technology India

    Schlumpbergers Technology India
    Schlumpbergers Technology India Coimbatore, India

    1 day ago

    Default job background
    Description

    Job Description :

    Assists MDM leads in the development of the enterprise MDM data model

    - Configures MDM tools to perform as required by MDM designs

    - Evaluates and recommends new and emerging MDM/DQ technologies, methodologies and standards

    - Ensures consistency and compatibility with all other system technology components

    - Develops the MDM data model and architecture

    - Utilizes a data modeling tool to develop "blueprints" for the Conceptual Data Model of the MDM architecture

    - Implements enterprise conceptual models to integrate master data from diverse data sources into conformed, high quality, and referentially sound enterprise master data model.

    - Implements master data modeling standards that includes naming standards, data quality indicators, data categorization, ETL attribute usage, data consistency and reuse, data quality.

    - Implements logical master data models using the data modeling tool for all layers in the MDM technical architecture framework.

    - Mitigates performance implications of various data modeling and architecture decisions at the logical and physical layer as related to ETL, ad hoc query access, and static reporting.

    - Reviews and validates master data models with stakeholders and subject matter experts.

    Essential qualifications :

    - 5 years of experience in data management development.

    2 years of experience in data modeling using CA Erwin or Embarcadero ER Studio

    - 2 years of experience in data warehousing required

    - Working understanding of Tableau or similar in memory analysis tool is preferred.

    - Experience with Agile development methodologies and concepts preferred.

    - Experience with the following disciplines is preferred: Data Warehousing, EAI, Metadata Management, Master Data Management (implementation and data stewardship), Data Quality Management, Relational Databases, Dimensional Databases, Semantics, Data Lifecycle Management, SQL, PL/SQL, UML, XML.

    Common Oilfield Operation procedures and the processes and procedures utilized to carry out Business Systems

    Good written communication and meeting facilitation skills.

    - Excellent written communication and meeting facilitation skills required

    Key competencies in data science technologies Upon entry, intermediate level of understanding in :

    Data requirements :

    - Data quality and compliance e.g. scorecard management

    - Data management principles

    - Business process management

    - Data stewardship, strategy and governance

    - Data factory capabilities

    - Data warehousing and business intelligence support

    - Rules (both DQ and MDM rules)

    - Mappings

    )
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