Key Responsibilities

Data Warehouse Architecture & Design:

• Lead the architecture, design, and implementation of scalable and high-performance data warehousing solutions using Microsoft Azure technologies (Azure Synapse Analytics, Azure Data Lake, SQL Server, etc.).
• Build and manage ETL/ELT pipelines for data ingestion and integration from multiple data sources.
• Design and implement data storage, retrieval, and archiving strategies for large-scale datasets.

Analytics & Reporting:

• Work closely with business stakeholders to understand reporting and analytics requirements and design solutions that enable effective decision-making.
• Leverage Microsoft Power BI and other tools to create interactive dashboards and reports for business intelligence.
• Perform complex data analysis and support data-driven insights that aid in strategic planning

AI & Predictive Modeling:

• Design, develop, and deploy machine learning models and AI solutions to enable predictive analytics and business forecasting.
• Utilize Microsoft Azure AI and ML services, such as Azure Machine Learning and Databricks, to implement models.
• Collaborate with management to identify business problems that can be addressed using AI models and predictive algorithms.

Data Science Collaboration:

• Act as a liaison between the data team and business stakeholders to ensure alignment of machine learning solutions with business objectives.
• Contribute to the development of data pipelines that support AI and ML model training and scoring.
• Implement automation strategies to optimize data science workflows and model deployment.

Project Leadership & Mentorship:

• Lead the development and deployment of data infrastructure projects from conception to production.
• Mentor junior data engineers and data scientists, providing guidance on best practices and the application of advanced analytics tools and techniques.
• Oversee the migration and integration of legacy systems into the new data warehouse architecture.

Continuous Improvement & Innovation:

• Stay up-to-date with the latest trends and advancements in data engineering, AI, and analytics.
• Drive the adoption of innovative technologies and techniques to improve data processes and predictive analytics capabilities.
• Continuously evaluate the performance and scalability of the data infrastructure to meet the evolving needs of the business.

Qualifications

Education & Experience:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum of 8+ years of experience in data architecture, data warehousing, and analytics in a large-scale environment.
• Proven track record of working with Microsoft technologies, specifically Azure Data Services (Azure Synapse Analytics, Azure SQL Database, Azure Data Lake, etc.).
• Experience in building, deploying, and maintaining AI models, including predictive modeling, machine learning, and statistical analysis