Chief Data Strategist

2 days ago

India beBeeData Full time US$ 2,00,000 - US$ 2,50,000
Senior Data Architect

This is a senior-level position that requires extensive experience in designing, implementing, and optimizing robust data warehousing platforms for the pharmaceutical industry.

The ideal candidate will have expertise in data architecture and management, with a strong understanding of how to ensure seamless integration of diverse data sources, maintain high standards of data quality, and governance. They will also be able to enable advanced analytics through the definition and management of semantic and common data layers.

Key Responsibilities:

  • Data Modeling: Design logical and physical data models to ensure efficient data storage and retrieval.
  • ETL Processes: Develop and optimize ETL processes to accurately and efficiently move data from various sources into the data warehouse.
  • Infrastructure Design: Plan and implement the technical infrastructure, including hardware, software, and network components.
  • Data Governance: Ensure compliance with regulatory standards and implement data governance policies to maintain data quality and security.
  • Performance Optimisation: Continuously monitor and improve the performance of the data warehouse to handle large volumes of data and complex queries.
  • Semantic Layer Definition: Define and manage the semantic layer architecture and technology stack to manage the lifecycle of semantic constructs including consumption into downstream systems.
  • Common Data Layer Management: Integrate data from multiple sources into a centralized repository, ensuring consistency and accessibility.

Qualifications:

  • Proven experience in data architecture and data warehousing, preferably in the pharmaceutical industry.
  • Strong knowledge of data modeling, ETL processes, and infrastructure design.
  • Experience with data governance and regulatory compliance in the life sciences sector.
  • Proficiency in using Axtria DataMAx or similar data management products.
  • Excellent analytical and problem-solving skills.
  • Strong communication and collaboration skills.

Preferred Skills:

  • Familiarity with advanced analytics and machine learning techniques.
  • Experience in managing semantic and common data layers.
  • Knowledge of FDA guidelines, HIPAA regulations, and other relevant regulatory standards.
  • Experience with generative AI technologies and their application in data warehousing

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