Data Warehouse Consultant

The Data Warehouse Consultant will design, build, and optimize scalable data warehouse and AI solutions. The ideal candidate has successfully delivered end-to-end data warehouses from the ground up, making key architectural decisions and implementing them effectively. This role requires someone who can quickly add value, work onsite with stakeholders, and demonstrate tangible results within the first few weeks.

This is a consultancy-based role for six (6) months.

Key Responsibilities

• Lead the end-to-end design and implementation of a scalable, high-performance data warehouse aligned with business needs and translate business requirements into dimensional models, ETL/ELT workflows, and analytics-ready datasets as well as recommend and implement suitable architectures, frameworks, and tools for data warehousing and integration.
• Develop, monitor, and maintain ETL/ELT processes using modern platforms and scripting, optimize data models, queries, and overall system performance, and ensure compliance with data governance, quality, security, and privacy standards.
• Oversee the consolidation and migration of legacy systems to modern cloud-based platforms, maintain accurate documentation (data dictionaries, lineage, process flows as well as provide expertise in BI/reporting integration to ensure consistency in analytics.
• Deliver quick wins and actionable insights within the first few weeks.
• Mentor and transfer knowledge to internal team members to ensure long-term capability.
  
  

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field (Master’s degree a plus).
• Minimum 8–10 years in data warehousing, business intelligence, or data engineering with proven track record of designing and implementing data warehouses from scratch, including key design decisions and ability to deliver rapid results and provide clear direction on priorities.
• Hands-on experience with cloud-based platforms (e.g., Azure Synapse, Microsoft Fabric, or similar) including strong SQL/T-SQL expertise in data modeling (star/snowflake schema) and performance tuning.
• Solid background in ETL/ELT development and scheduling (e.g., SSIS, Azure Data Factory), with exposure to data lakes and extensive experience integrating data from multiple sources, including ERP, SharePoint, and APIs including familiarity with BI tools (Power BI preferred) and data visualization best practices.
• Advanced SQL programming and performance optimization.
• Strong analytical and problem-solving abilities and excellent communication and stakeholder engagement skills.
• Knowledge of metadata management, data governance, and quality frameworks as well as ability to manage multiple priorities in a fast-paced environment.
  
  

Nice-to-Have

• Certifications in Azure Data Engineer, Microsoft Fabric, or similar platforms.
• Experience with scripting languages (e.g., Python) for data processing and automation.
• Knowledge of big data platforms and modern data stack tools.
• Industry experience in healthcare or distribution.
• Familiarity with AI/ML tools or implementation.