Enterprise Data Architect

Enterprise Data Architect

15-18 years
Not Specified

Job Description

  • Set technical vision, roadmap, architecture standards, and principles for large scale data initiative ensuring that the
  • business, application, data, and technology perspectives are in line with those of the organization.
  • Focus on delivering data solutions to improve decision-making, increase efficiency, and ultimately, transform data into actionable insights and products.
  • Align data architecture with enterprise strategy and architecture.
  • - Engage with the business to identify and define the required use cases, KPIs, and data assets of value to the business.
  • Support selection and implementation of data technologies
  • Write RFIs/RFQs/RFPs, estimate project cost, evaluate proposals, and help with the vendor evaluation/selection process.
  • Promote and standardize data governance, metadata management, data quality, data security, and best practices across the organization.
  • Architect conceptual and logical data models (dimensional/snowflake) and online analytical processing (OLAP)
  • Architect data warehouses, ETL solutions, and data lakes, for business intelligence, and advanced data analytics models (descriptive, predictive, and prescriptive)
  • Provide excellent advice to the data management team to ensure the team is delivering using proven software development methodologies and modern software best practices.
  • Plan and specify processes of data life cycle (capture, maintenance, synthesis, usage, publication, archiving and purging).

  • A minimum of a BS in Computer Science, information systems, or related field
  • At least 15 years of overall relevant professional experience
  • Expert in all aspects of enterprise data management (data strategy, governance, architecture, modeling/design,
  • Business intelligence & data warehouse, integration/ETL/data ingestion tools, master/reference data, metadata, advanced analytics, and data quality and security)
  • Experience using and preferably having implemented large-scale analytics/bi platforms.
  • Strong knowledge of software development methodologies and best practices.
  • Prior experience with big data platforms and AI is ideal.
  • Ability to operate in a fast-moving environment and deal with the complexity of multiple priorities and stakeholders.

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