Senior Business Intelligence Architect

12 hours ago

Gulbarga, Karnataka, India beBeeDataModeling Full time US$ 1,50,000 - US$ 2,00,000
Job Title: Senior Data Engineer - Data Modeler

Description:

The Data Modeler plays a pivotal role in the organization's data management strategy, responsible for designing and implementing data capture and transformation processes. Collaborating closely with cross-functional teams, they analyze and understand datasets to create source-to-target mappings and develop data dictionaries.

This is an ideal opportunity for experienced professionals who have extensive knowledge in conceptual, logical, and physical data modeling, as well as a solid understanding of data warehousing principles and architecture. Proficiency in one or more ETL tools and data ingestion frameworks is essential, along with expertise in leading large teams and managing complex projects.

The Data Modeler will work collaboratively with business stakeholders, data owners, business analysts, and architects to design and develop next-generation data platforms. Key responsibilities include defining data modeling best practices, optimizing data models, and ensuring implementation across projects.

  • Design, develop, and implement highly scalable data capture and transformation processes.
  • Suggest optimal modeling approaches based on client requirements and target architecture.
  • Analyze and understand datasets to guide team members in creating source-to-target mapping and data dictionaries, capturing all relevant details.
  • Profile data sets to generate relevant insights.
  • Define data modeling best practices and ensure implementation across projects.
  • Optimize data models, working with data engineers to define ingestion logic, ingestion frequency, and data consumption patterns.
  • Work with QA teams to define the right testing strategy.
  • Drive automation in modeling activities.
  • Collaborate with business stakeholders, data owners, business analysts, and architects to design and develop next-generation data platforms.
  • Manage data modeling repository, and data modeling process, and support model-driven development.
  • Define and govern data modeling/design standards, tools, best practices, and related development methodologies.
  • Champion data lineage, metadata management, and data quality analysis processes.
  • Collaborate with business data analysts to design and model business intelligence semantic layers for optimized information access.
  • Expand and grow existing data platform capabilities to solve new data problems and challenges.
  • Ensure all automated processes preserve data integrity by managing alignment of data availability and integration processes.
  • Identify opportunities for new data acquisition and new uses for existing data resources.
  • Research and make recommendations for new data management technologies and software engineering practices.

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