SLB - MDM Developer - Data Warehousing

4 weeks ago


CoimbatorePune, IN Schlumpbergers Technology India Full time

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

(ref:hirist.tech)

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