Azure Data Architect

Key Responsibilities:

Data Architecture & Engineering: Design, implement, and maintain a scalable data architecture on Azure, leveraging technologies like Data Lake, Data Factory, and Databricks. Optimize data pipelines for performance, reliability, and cost-effectiveness.
AI Integration: Collaborate closely with data scientists and AI engineers to extract and prepare datasets for AI models. Implement data governance and security measures to ensure data integrity and compliance.
Data Governance: Establish and enforce data governance policies, standards, and procedures. Ensure data quality, consistency, and accessibility across the organization.
Team Leadership: Manage and mentor a team of data engineers and analysts, fostering a culture of innovation and excellence.
Stakeholder Management: Build strong relationships with business stakeholders to understand their data needs and translate them into actionable data solutions.
Performance Optimization: Continuously monitor and optimize data platform performance, identifying and resolving bottlenecks.
Emerging Technologies: Stay updated with the latest advancements in data architecture, AI, and machine learning, and incorporate them into our data strategy.

Required Skills and Experience:

10-15 years of experience in data architecture, with a deep understanding of data warehousing, data lakes, and big data technologies.
Strong proficiency in Azure data services, including Data Factory, Data Lake, Databricks, and SQLSQL Database.
Expertise in data modeling, ETL/ELT processes, and BI tools.
Proven ability to design and implement complex data solutions in cloud environments.
Strong understanding of data governance, security, and compliance frameworks.
Proven experience in leading and managing data engineering teams.
Demonstrated ability to collaborate effectively with data scientists and AI engineers.
Excellent communication and interpersonal skills, with a focus on stakeholder management.

Preferred Qualifications:

Experience with AI/ML frameworks (TensorFlow, PyTorch) and their integration with data platforms.
Certifications in Azure data technologies (e.g., Azure Data Engineer Associate).
Experience with cloud-native data platforms and serverless computing.