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 up-to-date 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

- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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

- 12–15+ 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

- Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or related field.
- Master’s degree (MBA, Data Science, Analytics, or similar) preferred.

📌 Senior Manager - Data & AI Solution Management (Bengaluru)
🏢 Fresenius Medical Care
📍 Bengaluru