Sr. Manager – Data & AI Architecture

Position Purpose:

To design and implement enterprise data architecture, governance, and integration frameworks that support both internal data operations and client-facing solutions. This role is integral in ensuring scalable, secure, and high-performing data architectures that align with business intelligence, analytics, and AI-driven initiatives. To drive best practices in data modeling, cloud data platforms, data lakes, and real-time data processing while working closely with engineering, AI, and business teams to enable data-driven decision-making. Additionally, this role will serve as an AI Architect, guiding AI driven solutions by aligning Ai strategy with enterprise goals.

Role Description

1. Data Architecture Strategy & Design
2. Cloud & Big Data Ecosystem Integration
3. Data Governance & Compliance
4. Data Integration & Interoperability
5. AI & Advanced Analytics Enablement
6. Leadership & Team Development

Job Specific Knowledge and Skills:

• Expertise in enterprise data architecture, cloud data platforms, and big data technologies.
• Strong knowledge of data modeling, data lakes, data warehouses, and real-time processing architectures.
• Proven ability to design scalable, secure, and high-performance data solutions.
• Experience in data governance, metadata management, and regulatory compliance.
• Strong background in ETL/ELT processes, API-based data integrations, and event-driven architectures.
• Ability to optimize AI/ML pipelines through structured data architecture frameworks.
• Proficiency in SQL, Python, Spark, and cloud-based data engineering tools.
• Strong leadership in team development, cross-functional collaboration, and stakeholder engagement.
• Ability to drive innovation in data management, enabling AI and advanced analytics capabilities.
• Experience in cost optimization and performance tuning for cloud-based data solutions.

Preferred Qualifications & Experience:

1. Bachelor’s or Masters degree in Computer Science, Data Engineering, or related field.
2. 10+ years of experience in data architecture, big data engineering, or cloud data solutions.
3. Proven expertise in Azure, AWS, and/or Google Cloud-based data ecosystems (with certifications, Azure required).
4. Experience with data modeling tools, metadata management, and data governance platforms.
5. Strong understanding of data mesh, data fabric, and decentralized data architectures.
6. Background in leading and managing data architecture teams in enterprise environments.
7. Familiarity with BI/analytics tools such as Power BI, Tableau, or Looker.
8. Experience in supporting AI/ML workflows with structured, high-quality data pipelines.