📍 Job Overview

Job Title: GenAI Python Systems Engineer – Senior Manager
Company: PwC
Location: Chicago - One North Wacker Drive, IL-Chicago, NC-Raleigh, NC-Charlotte, OH-Cincinnati, OH-Cleveland
Job Type: Full-Time
Category: Senior Manager - Data Engineering & AI
Date Posted: 2025-06-11
Experience Level: 10+ years
Remote Status: Remote OK

🚀 Role Summary

Senior Manager leading data engineering and AI teams, focusing on leveraging advanced technologies and techniques to design and develop robust data solutions for clients.
Strategic Advisor driving quality results, motivating teams, and coaching others to solve complex problems.
Expertise in Python, SQL, AI techniques, and machine learning workflows, with a strong background in data architecture, data governance, and software development workflows.

💻 Primary Responsibilities

Data Infrastructure & Systems: Develop and implement data pipelines, data integration, and data transformation solutions. Design and build data infrastructure and systems to enable efficient data processing and analysis.
Data Architecture: Design and manage data warehouses and data lakes, ensuring data is organized, accessible, and compliant with data governance and security policies. Collaborate with stakeholders to understand their data requirements and translate them into technical solutions.
AI & Machine Learning: Leverage AI techniques to enhance LLMs, such as AI Agents and Retrieval-Augmented Generation (RAG). Optimize LLM outputs through prompt engineering. Experience with machine learning and data science workflows is a plus.
Cloud & Data Services: Develop and deploy scalable data storage solutions using AWS, Azure, and GCP services. Implement data integration solutions using relevant services from these cloud providers. Optimize cloud resources for cost, performance, and scalability.
Team Leadership & Collaboration: Lead and mentor team members, fostering a positive working environment. Collaborate with team members to understand personal and team roles, and contribute to a positive working environment by building proven relationships.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Information Technology, or a related field. Pursuit of advanced degrees or certifications is a plus.

Experience: 10+ years of experience in data engineering, AI, and machine learning, with a strong focus on Python and SQL. Proven experience in high software quality through developer-led testing, validation, and best practices.

Required Skills:

Strong proficiency in Python and SQL
Experience with FastAPI and AI techniques (AI Agents, RAG, etc.)
Knowledge of data integration solutions (AWS Glue, AWS Lambda, Azure Data Factory, etc.)
Experience with data warehouses, data lakes, and data architecture strategies
Strong analytical, problem-solving, and communication skills
Ability to work independently and as part of a team in a fast-paced environment

Preferred Skills:

Experience with machine learning and data science workflows
Knowledge of software development workflows and CI/CD pipelines
Experience with Docker, infrastructure as code (IaC) deployments, and cloud-based technology skills
Familiarity with data governance and security best practices

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate proficiency in Python, SQL, and AI techniques through relevant projects and case studies.
Showcase experience in data architecture, data integration, and data transformation solutions.
Highlight expertise in cloud services (AWS, Azure, GCP) and data storage solutions.
Display strong analytical and problem-solving skills through real-world examples.

Technical Documentation:

Document data or system models, flow diagrams, and architecture guidelines for past projects.
Include code comments, version control, and deployment processes in your portfolio.
Showcase understanding of data governance and security policies through relevant documentation.

💵 Compensation & Benefits

Salary Range: $130,000 - $256,000 per year, plus an annual discretionary bonus.

Benefits:

Medical, dental, and vision insurance
401k plan
Holiday pay
Vacation and personal/family sick leave
Other benefits as listed on the company's benefits-at-a-glance webpage

Working Hours: Up to 40 hours per week, with the possibility of working up to 80% travel.

🎯 Team & Company Context

Company Culture:

Industry: Data, Analytics & AI
Company Size: Large (global professional services network)
Founded: 1854 (as PwC, but with roots tracing back to the 1840s)

Team Structure:

Lead and manage data engineering and AI teams, collaborating with various stakeholders, including business leaders, designers, and marketers.
Work with cross-functional teams to deliver quality results and drive business growth.
Foster a positive working environment by building proven relationships with team members.

Development Methodology:

Leverage modern, cloud-based technology skills and emerging trends to apply in solution architectures.
Collaborate and contribute as a team member, understanding personal and team roles, and proactively seeking guidance, clarification, and feedback.
Prioritize and handle multiple tasks, research and analyze pertinent client, industry, and technical matters, and communicate effectively in written and verbal formats to various audiences.

Company Website: https://www.pwc.com/

📝 Enhancement Note: PwC is a global professional services network with a strong focus on data-driven decision-making and innovative technology solutions. As a Senior Manager in data engineering and AI, you will play a crucial role in driving the company's data strategy and helping clients transform their businesses through advanced data solutions.

📈 Career & Growth Analysis

Web Technology Career Level: Senior Manager - Data Engineering & AI

Lead and manage data engineering and AI teams, driving quality results and motivating team members.
Collaborate with stakeholders to understand their data requirements and translate them into technical solutions.
Develop and sustain high-performing, diverse, and inclusive teams, applying sound judgment and making difficult decisions as needed.

Reporting Structure: Report directly to the relevant business unit leader or partner, depending on the specific team and project requirements.

Technical Impact: Influence data-driven decision-making and business growth by designing and implementing robust data solutions that enable efficient data processing and analysis.

Growth Opportunities:

Technical Leadership: Develop and refine expertise in data engineering, AI, and machine learning. Stay up-to-date with emerging trends and technologies in the field.
Career Progression: Pursue career advancement opportunities within PwC's global professional services network, such as moving into a principal or director role, or exploring other areas of interest within the company.
Mentoring & Coaching: Provide coaching and feedback to team members, helping them develop their skills and advance in their careers.

📝 Enhancement Note: As a Senior Manager in data engineering and AI at PwC, you will have the opportunity to grow both technically and professionally. By leading and managing teams, driving quality results, and collaborating with stakeholders, you can make a significant impact on the company's data strategy and help clients transform their businesses through advanced data solutions.

🌐 Work Environment

Office Type: Modern, collaborative office spaces with a focus on technology and innovation.

Office Location(s): Chicago - One North Wacker Drive, IL-Chicago, NC-Raleigh, NC-Charlotte, OH-Cincinnati, OH-Cleveland

Workspace Context:

Collaborative Environment: Work closely with cross-functional teams, including business leaders, designers, and marketers, to deliver quality results and drive business growth.
Development Tools: Leverage modern development tools, multiple monitors, and testing devices to ensure efficient data processing and analysis.
Knowledge Sharing: Foster a culture of knowledge sharing, technical mentoring, and continuous learning within the team.

Work Schedule: Up to 40 hours per week, with the possibility of working up to 80% travel, depending on project requirements and business needs.

📝 Enhancement Note: PwC offers a modern, collaborative work environment that fosters innovation and technology-driven solutions. As a Senior Manager in data engineering and AI, you will have the opportunity to work with cutting-edge tools and technologies, collaborate with diverse teams, and make a significant impact on the company's data strategy and client projects.

📄 Application & Technical Interview Process

Interview Process:

Technical Preparation: Brush up on Python, SQL, and AI techniques. Review relevant projects and case studies, focusing on data architecture, data integration, and data transformation solutions.
Portfolio Review: Prepare a comprehensive portfolio showcasing your expertise in data engineering, AI, and machine learning. Highlight your ability to design and implement robust data solutions that enable efficient data processing and analysis.
Team Interaction: Demonstrate strong communication skills and the ability to collaborate effectively with cross-functional teams. Showcase your leadership skills and ability to motivate team members.
Final Evaluation: Discuss your technical impact on past projects and your vision for driving quality results and business growth at PwC.

Portfolio Review Tips:

Portfolio Structure: Organize your portfolio into clear sections, highlighting your expertise in data engineering, AI, and machine learning. Include relevant projects, case studies, and technical documentation.
Live Demos: Prepare live demos of your projects, showcasing your ability to design and implement robust data solutions that enable efficient data processing and analysis.
Technical Depth: Demonstrate a deep understanding of Python, SQL, and AI techniques, as well as relevant cloud services (AWS, Azure, GCP) and data storage solutions.

Technical Challenge Preparation:

Data Architecture: Brush up on data architecture principles and best practices. Be prepared to discuss your approach to designing and managing data warehouses, data lakes, and data integration solutions.
AI & Machine Learning: Review AI techniques, such as AI Agents and Retrieval-Augmented Generation (RAG), and machine learning workflows. Be prepared to discuss your experience with optimizing LLM outputs through prompt engineering.
Cloud Services: Familiarize yourself with relevant cloud services (AWS, Azure, GCP) and data storage solutions. Be prepared to discuss your experience with developing and deploying scalable data storage solutions.

ATS Keywords: Python, SQL, AI, Machine Learning, Data Engineering, Data Architecture, Cloud Services, AWS, Azure, GCP, Data Integration, Data Transformation, Leadership, Collaboration, Team Management, Stakeholder Communication

📝 Enhancement Note: As a Senior Manager in data engineering and AI at PwC, you will be expected to demonstrate a strong technical background in data engineering, AI, and machine learning, as well as excellent leadership and communication skills. By preparing thoroughly for the interview process and showcasing your expertise in your portfolio, you can increase your chances of success in securing the role.

🛠 Technology Stack & Web Infrastructure

Frontend Technologies: Not applicable (focus on data engineering and AI)

Backend & Server Technologies:

Python (core programming language)
SQL (relational databases)
FastAPI (web framework for building APIs)
AI techniques (AI Agents, Retrieval-Augmented Generation, etc.)
Machine learning and data science workflows

Development & DevOps Tools:

Docker (containerization platform)
Infrastructure as code (IaC) deployments (AWS CloudFormation, Azure Resource Manager templates, Terraform)
Cloud-based technology skills (AWS, Azure, GCP)
Version control systems (Git, GitHub, etc.)
CI/CD pipelines (Jenkins, GitLab CI/CD, etc.)
Monitoring tools (Prometheus, Grafana, etc.)

📝 Enhancement Note: As a Senior Manager in data engineering and AI at PwC, you will be expected to have a strong technical background in Python, SQL, and AI techniques, as well as experience with relevant cloud services (AWS, Azure, GCP) and data storage solutions. Familiarity with development tools, version control systems, and CI/CD pipelines will also be crucial for success in the role.

👥 Team Culture & Values

Web Development Values:

Quality & Innovation: Pursue high software quality through developer-led testing, validation, and best practices. Stay up-to-date with emerging trends and technologies in data engineering, AI, and machine learning.
Collaboration: Work closely with cross-functional teams, including business leaders, designers, and marketers, to deliver quality results and drive business growth.
Knowledge Sharing: Foster a culture of knowledge sharing, technical mentoring, and continuous learning within the team.
Client Focus: Understand and address client data requirements and translate them into technical solutions that drive business growth.

Collaboration Style:

Cross-Functional Integration: Work closely with business leaders, designers, and marketers to deliver quality results and drive business growth.
Code Review Culture: Encourage a culture of code review and peer programming to ensure high software quality and knowledge sharing.
Technical Mentoring: Provide coaching and feedback to team members, helping them develop their skills and advance in their careers.

📝 Enhancement Note: As a Senior Manager in data engineering and AI at PwC, you will be expected to embody the company's values of quality, innovation, collaboration, and client focus. By fostering a culture of knowledge sharing, technical mentoring, and continuous learning, you can help drive the team's success and make a significant impact on the company's data strategy and client projects.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Complexity: Design and implement data solutions that can handle large, complex datasets, ensuring efficient data processing and analysis.
Emerging Technologies: Stay up-to-date with emerging trends and technologies in data engineering, AI, and machine learning, and integrate them into your work as needed.
Scalability & Performance: Develop and deploy scalable data storage solutions using AWS, Azure, and GCP services, optimizing cloud resources for cost, performance, and scalability.
Data Governance & Security: Ensure data architecture is compliant with data governance and security policies, protecting sensitive data and maintaining data integrity.

Learning & Development Opportunities:

Technical Skill Development: Pursue advanced certifications or training in data engineering, AI, and machine learning to deepen your expertise and stay relevant in the field.
Conference Attendance: Attend industry conferences and events to network with peers, learn about emerging trends, and gain new insights into data engineering, AI, and machine learning.
Technical Mentorship: Seek mentorship opportunities from experienced professionals in data engineering, AI, and machine learning to gain valuable insights and guidance for your career development.

📝 Enhancement Note: As a Senior Manager in data engineering and AI at PwC, you will face technical challenges related to data complexity, emerging technologies, scalability, and data governance. By staying up-to-date with industry trends, pursuing continuous learning opportunities, and seeking mentorship from experienced professionals, you can overcome these challenges and drive the team's success in delivering quality data solutions to clients.

💡 Interview Preparation

Technical Questions:

Data Architecture: Discuss your approach to designing and managing data warehouses, data lakes, and data integration solutions. Describe your experience with data governance and security best practices.
AI & Machine Learning: Explain your understanding of AI techniques, such as AI Agents and Retrieval-Augmented Generation (RAG), and machine learning workflows. Describe your experience with optimizing LLM outputs through prompt engineering.
Cloud Services: Discuss your experience with relevant cloud services (AWS, Azure, GCP) and data storage solutions. Describe your approach to developing and deploying scalable data storage solutions, optimizing cloud resources for cost, performance, and scalability.

Company & Culture Questions:

Company Culture: Demonstrate your understanding of PwC's values and culture, highlighting your ability to collaborate effectively with cross-functional teams and drive quality results.
Data-Driven Decision-Making: Explain your approach to leveraging data-driven decision-making to drive business growth and deliver quality results to clients.
Stakeholder Communication: Describe your experience working with stakeholders to understand their data requirements and translate them into technical solutions that drive business growth.

Portfolio Presentation Strategy:

Live Demos: Prepare live demos of your projects, showcasing your ability to design and implement robust data solutions that enable efficient data processing and analysis.
Technical Walkthroughs: Provide detailed walkthroughs of your projects, highlighting your expertise in data engineering, AI, and machine learning.
User Experience: Demonstrate your understanding of user experience principles and how they apply to data-driven decision-making and business growth.

📌 Application Steps

To apply for this Senior Manager - Data Engineering & AI position at PwC:

Update Your Resume: Highlight your experience in data engineering, AI, and machine learning, as well as your leadership and communication skills. Include relevant keywords and phrases to optimize your resume for the ATS.
Prepare Your Portfolio: Organize your portfolio into clear sections, highlighting your expertise in data engineering, AI, and machine learning. Include relevant projects, case studies, and technical documentation.
Practice Technical Interview Questions: Brush up on your technical skills in data engineering, AI, and machine learning, and practice answering common interview questions related to these topics.
Research PwC: Learn about PwC's company culture, values, and data-driven decision-making approach. Prepare thoughtful questions to ask during the interview process to demonstrate your interest in the role and the company.

📝 Enhancement Note: As a Senior Manager in data engineering and AI at PwC, you will be expected to demonstrate a strong technical background, excellent leadership and communication skills, and a deep understanding of the company's data-driven decision-making approach. By following these application steps and preparing thoroughly for the interview process, you can increase your chances of success in securing the role.

GenAI Python Systems Engineer –Senior Manager