We are seeking a
Senior / Head of AI & Data Architecture to lead the design, implementation, and evolution of our enterprise data and AI ecosystem. This role will be responsible for defining scalable data architectures, driving AI and analytics innovation, and aligning data engineering initiatives with business strategy.
The ideal candidate is a hands-on technical leader with deep expertise in
data architecture, ETL/ELT pipelines, cloud data platforms, governance, and emerging AI technologies, combined with strong stakeholder management and pre-sales exposure.
Key Responsibilities
Data Architecture & Engineering Leadership
- Design and implement scalable data models, databases, and data flow architectures to meet complex business and technical requirements.
- Own and evolve the organization's data architecture framework, ensuring alignment with business goals and industry best practices.
- Architect and optimize data storage platforms, including operational databases, data warehouses, and data lakes for performance, scalability, and reliability.
- Lead the design and implementation of robust ETL/ELT pipelines, ensuring accurate, reliable, and near-real-time data integration across platforms.
Data Governance, Security & Compliance
- Define and enforce data quality standards, data lifecycle management, and governance frameworks.
- Ensure compliance with data security, privacy, and regulatory requirements (e.g., GDPR, DPDP, industry-specific regulations).
- Establish best practices for metadata management, lineage, auditability, and access control across the data ecosystem.
AI, Analytics & Innovation
- Drive innovation by evaluating and adopting AI, Machine Learning, and Advanced Analytics technologies.
- Lead R&D initiatives to develop innovative Data & AI products, accelerators, and solutions.
- Partner with analytics and BI teams to support dashboarding, reporting, and advanced analytical use cases.
- Stay current with emerging trends in Data Engineering, AI platforms, cloud-native analytics, and automation, translating them into business value.
Engineering Excellence & Best Practices
- Evangelize and implement data engineering best practices, including CI/CD, automation, testing, observability, and version control.
- Establish standards for scalable, reliable, and future-proof architectures.
- Proactively identify opportunities for process optimization, cost efficiency, and platform modernization.
Collaboration, Leadership & Stakeholder Engagement
- Collaborate closely with data engineers, software developers, business analysts, product teams, and leadership stakeholders.
- Provide technical leadership, mentorship, and architectural guidance to engineering and data teams.
- Communicate complex data and AI concepts to both technical and non-technical stakeholders with clarity and confidence.
- Build strong stakeholder relationships and deliver solutions that create measurable business impact.
Pre-Sales & Client Engagement
- Partner with business and sales teams during pre-sales and solutioning activities.
- Translate client requirements into data-driven, AI-enabled solutions, providing technical credibility and thought leadership.
- Support proposal development, architecture design, and client presentations as a subject-matter expert.
Required Qualifications
- 12–18+ years of experience in Data Engineering, Data Architecture, Analytics, or AI-related roles
- Strong hands-on experience with:
- Data modelling and enterprise data architecture
- ETL/ELT frameworks and large-scale data pipelines
- Data warehouses, data lakes, and cloud data platforms
- Proven leadership experience managing and mentoring data and engineering teams
- Solid understanding of data governance, quality, security, and compliance
- Experience driving cloud-native data solutions (AWS, Azure, GCP preferred)
- Strong communication and stakeholder management skills
Preferred Skills & Experience
- Exposure to AI/ML platforms, MLOps, and AI-driven product development
- Experience with modern BI and analytics tools
- Background in consulting, system integration, or enterprise digital transformation
- Pre-sales, solution architecture, or client-facing experience
- Ability to operate in a fast-paced, multi-project, and innovation-driven environment
Skills: ai/ml,data architecture,etl,cloud
