• Lead the design and delivery of modern data platforms and AI solutions, aligned with client business strategy.

• Translate complex business challenges into scalable data and AI architectures.

• Act as a trusted advisor to clients on data transformation, cloud strategy, and AI adoption.

• Support and lead pre-sales activities, including solution design, proposals, demos, and client workshops.

Delivery & Technical Excellence

• Serve as workstream lead, Data Architect, or Technical Project Manager across engagements.

• Drive the end-to-end implementation lifecycle, ensuring quality, scalability, and performance.

• Oversee and review engineering outputs, ensuring best practices, optimization, and governance.

• Lead architectural reviews and provide guidance on solution design, deployment, and integration.

People Development & Leadership

• Mentor and develop junior team members, fostering technical capability and professional growth.

• Contribute to building a strong internal Data & AI community of practice.

• Promote a culture of collaboration, innovation, and continuous learning.

Business Development & Growth

• Support the growth of PwC’s Data & AI portfolio through relationship building and opportunity identification.

• Build and maintain long-term client relationships that create sustained value.

• Contribute to firm initiatives and uphold PwC’s code of ethics and professional standards.

Experience & Credentials

• 8–10+ years of experience in data architecture, data engineering, and AI solution design.

• Proven track record in designing and delivering modern data platforms, pipelines, data models, and governance frameworks.

• Strong experience in pre-sales and solutioning, including proposals, tenders, and client presentations.

• Minimum 5 years of hands-on experience with Databricks and Microsoft Azure Data Services / Microsoft Fabric.

• Experience delivering end-to-end Databricks implementations (minimum 5 full project lifecycles).

• Mandatory cloud solution architect certification (e.g., Azure, AWS, or GCP).

Technical Expertise

• Strong capabilities in cloud architecture, including scalable, highly available, and fault-tolerant systems.

• Hands-on experience with PySpark / Apache Spark and modern data engineering practices.

• Expertise in data platform architecture, cloud data ecosystems, and data governance frameworks.

• Ability to evaluate requirements and provide end-to-end architectural recommendations.

Leadership & Consulting Skills

• Demonstrated ability to lead complex transformation programs and technical teams.

• Strong stakeholder management skills with the ability to influence at senior client levels.

• Commercial mindset with experience driving business development and client engagement.