Industry/Sector

Specialism

Management Level

Job Description & Summary

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As a Gen AI - Manager you will lead client support work within our Data & Analytics Engineering practice, focusing on data engineering solutions that support cloud engineering, data modernization, and product innovation efforts. As a Manager you will guide teams, coach junior professionals, and take accountability for planning, reviewing, and delivering assigned workstreams while applying sound judgment to complex problems and adapting to changing client needs. In this role at PwC Acceleration Center India, you will contribute to the design and delivery of GenAI-enabled solutions, coordinate task execution across multiple contributors, and help maintain clear timelines, practical deliverables, and consistent communication across the engagement.

Responsibilities

- Leading Gen AI data engineering workstreams across client engagements and translating product innovation priorities into practical delivery plans
- Managing project scope, timelines, and milestones for data modernization initiatives that use cloud data platforms, pipeline automation, and scalable architecture patterns
- Guiding teams in building, testing, and tuning data pipelines, data models, and warehouse solutions across Snowflake, Databricks, Azure Data Factory, and Apache Airflow
- Reviewing technical deliverables for data quality, transformation logic, security controls, and performance optimization across complex data environments
- Coaching junior team members on data engineering methods, reusable design patterns, and day-to-day delivery practices
- Identifying opportunities to use AI fluency, data architecture, and digital tooling to improve modernization outcomes and streamline delivery
- Communicating progress, risks, and technical tradeoffs to client stakeholders and internal leaders in a clear and organized way
- Applying analytical thinking to diagnose data issues, troubleshoot database behavior, and support scalable integration across platforms
- Supporting accountable delivery across multiple workstreams while balancing client needs, team capacity, and delivery timelines

What You Must Have

- At least a Bachelor's degree
- At least 8 years of experience
- Oral and written proficiency in English required

- Python Proficiency: Minimum 3 years of hands-on experience building applications with Python. 

- Scalable System Design: Solid understanding of designing and architecting scalable Python applications, particularly for Gen AI use cases, with a strong understanding of various components and systems architecture patterns to make cohesive and decoupled, scalable applications. 

- Web Frameworks: Familiarity with Python web frameworks (Flask, FastAPI) for building web applications around AI models. 

- Modular Design & Security: Demonstrated ability to design applications with modularity, reusability, and security best practices in mind (session management, vulnerability prevention, etc.,). 

- Cloud-Native Development: Familiarity with cloud-native development patterns and tools (e.g., REST APIs, microservices, serverless functions). 

- Cloud Deployments: Experience deploying and managing containerized applications on Azure/AWS (Azure Kubernetes Service, Azure Container Instances, or similar). 

- Version Control (Git):  Strong proficiency in Git for effective code collaboration and management. 

- CI/CD: Knowledge of continuous integration and deployment (CI/CD) practices on cloud platforms. 

What Sets You Apart

- Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
- Demonstrating management of data modernization workstreams across client engagements
- Leveraging Gen AI fluency to shape data engineering solutions
- Utilizing cloud data platforms such as AWS, Azure, or Snowflake
- Applying Databricks, Airflow, or data pipeline automation skills
- Mentoring teams through agile delivery and feedback cycles

Travel Requirements

Job Posting End Date