Senior Manager Data & AI Solution Management

Sr. Manager Data & AI Solution Management

Role Overview

The Sr. Manager Data & AI Solution Management is a people leadership and execution role responsible for building leading and scaling a high-performing multidisciplinary data and AI COE in Global Business Services. This role oversees end-to-end service delivery and maintenance of enterprise data analytics AI/ML and Generative AI solutions ensuring alignment with business priorities governance standards and modern cloud architectures.

The position manages a team of senior professionals across analytics engineering AI governance and service management driving service delivery while ensuring operational excellence scalability and responsible AI practices across AWS and Azure ecosystems.

Key Responsibilities

1. Strategic Leadership & Delivery

• Define and execute the enterprise Data & AI strategy aligned with business goals and digital transformation initiatives.
• Lead the design and delivery of end-to-end data analytics ML and GenAI solutions ensuring business value realization.
• Establish scalable frameworks for AI/ML data platforms analytics and governance across the organization.
• Drive adoption of modern data architecture patterns including cloud-native multi-cloud and hybrid ecosystems.

2. Team Leadership & Talent Development

• Lead mentor and develop a team of a medium group senior professionals across data AI engineering and analytics domains.
• Build a high-performance culture focused on innovation accountability and continuous improvement.
• Define career paths skill development and succession planning for all roles.
• Foster cross-functional collaboration between business engineering and analytics teams.

3. Data & AI Solution Delivery Oversight

• Oversee delivery of solutions:
  • Data engineering pipelines and platforms (Databricks Snowflake AWS Azure)
  • Data modeling and architecture frameworks
  • Advanced analytics and BI solutions
  • Machine Learning and Generative AI solutions (LLMs RAG copilots)
• Ensure integration of solutions into enterprise systems and workflows.
• Drive Agile delivery models and ensure timely high-quality releases.

4. AI ML & GenAI Enablement

• Establish scalable practices for:
  • Machine Learning lifecycle (MLOps)
  • Generative AI solution design (prompt engineering RAG architectures)
  • AI evaluation monitoring and optimization
• Ensure AI initiatives are:
  • Business-driven
  • Measurable
  • Production-ready
• Partner with teams to embed AI capabilities into enterprise applications.

5. Data Governance Quality & Compliance

• Ensure robust implementation of:
  • Data governance frameworks (metadata lineage cataloging)
  • Data quality and monitoring standards
  • Security privacy and regulatory compliance controls
• Promote trusted governed and high-quality data assets across the organization.
• Enable responsible AI practices including explainability fairness and compliance.

6. Stakeholder Engagement & Business Alignment

• Act as a trusted advisor to business and technology leaders.
• Translate complex business needs into scalable data and AI solutions.
• Drive adoption and value realization of delivered solutions.
• Lead executive reporting on program progress outcomes and KPIs.

7. Platform Architecture & Technology Oversight

• Govern enterprise data and AI platforms including:
  • Databricks Snowflake
  • AWS and Azure data services
  • SageMaker Amazon Bedrock Azure OpenAI
• Ensure solutions are:
  • Scalable secure and cost-efficient
  • Designed for performance and reliability
• Drive standardization automation and DevOps/CI-CD practices.

8. Service Management & Operational Excellence

• Partner with the DAIS Sr. Service Manager to ensure:
  • Stable operations of data and AI platforms
  • SLA adherence and incident management
  • Continuous improvement and monitoring frameworks
• Implement metrics-driven service management practices.

Required Skills & Experience

Leadership & Functional Expertise

• 1215 years of experience in data analytics AI/ML or engineering roles with at least 5 years in leadership positions.
• Proven experience managing cross-functional teams across data analytics and AI domains.
• Strong understanding of:
  • Data engineering modeling and analytics
  • Machine learning and MLOps
  • Generative AI (LLMs RAG copilots)
  • Data governance and compliance frameworks

Technical Expertise

• Hands-on knowledge of:
  • Cloud platforms: AWS and/or Azure
  • Data platforms: Databricks Snowflake
  • AI/ML platforms: SageMaker Azure ML Bedrock
• Familiarity with:
  • Data pipelines ETL/ELT and streaming architectures
  • Data modeling techniques (dimensional relational etc.)
  • AI/ML lifecycle model evaluation and deployment
  • Governance tools metadata and lineage frameworks

Business & Stakeholder Skills

• Strong ability to translate business problems into technical solutions.
• Excellent communication and executive presentation skills.
• Proven ability to influence senior stakeholders and drive transformation.
• Experience working in Agile and product-driven environments.

Education

• Bachelors degree in Computer Science Engineering Data Science Information Systems or related field.
• Masters degree (MBA Data Science Analytics or similar) preferred.

Required Experience:

Senior Manager

Employment Type : Full-Time
Experience: years
Vacancy: 1