10626- Data Warehousing Consultant

Job Posting

3 DAYS  DC

Ideally they want someone with Azure Data Factory experience (ADF) as the main ETL tool they would be using, but because they are transitioning from SAP, SAP BODS could work as well. Really looking for someone with experience with Azure SQL database as well as opposed to just regular SQL database! They should have experience with Azure data lakes as that kind of goes hand in hand with ADF

Candidate should have hands-on experience on working in Cloud Based Data warehouse Solution with below capabilities:

• Data Modeling:
  Design and implement data models based on business requirements. Optimize and normalize database structures for efficient data storage and retrieval.
• Database Development:
  Develop and maintain database schemas, tables, indexes, and views. Write efficient and optimized SQL queries for data manipulation and retrieval.
• ETL (Extract, Transform, Load):
  Design and implement ETL processes to extract data from various sources, transform it as needed, and load it into the target databases. Experience on any ETL tools like Azure ADF/SAP BODS
• Data Integration:
  Integrate data from diverse sources and systems to create a unified view. Implement data integration solutions for real-time or batch processing. Extensive experience in data analysis using SQL, Python
• Data Warehousing:
  Design and develop data warehouses to support business intelligence and reporting needs. Optimize data warehouse performance and ensure scalability.
• Data Security:
  Implement and maintain security measures to protect sensitive data. Monitor and audit data access to ensure compliance with security policies.
• Performance Tuning:
  Identify and resolve performance issues in databases and data processing pipelines. Optimize queries and processes for better performance.
• Collaboration:
  
  Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders. Communicate effectively to understand and address data requirements.
• Continuous Learning:
  Stay updated on industry trends, emerging technologies, and best practices in data development.
• Problem Solving:
  Identify and resolve data-related issues and challenges. Troubleshoot and debug issues in databases and data processing systems.