Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member’s unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Analyse and identify the linkages and interactions between the component parts of an entire system.
• Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
• Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
• Develop skills outside your comfort zone, and encourage others to do the same.
• Effectively mentor others.
• Use the review of work as an opportunity to deepen the expertise of team members.
• Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.

As part of the Data and Analytics Engineering team, you lead the development and implementation of data architecture strategies that align with business needs. As a Manager, you guide and mentor your team, delivering top-quality solutions while leveraging team strengths and managing performance to meet client expectations. You play a crucial role in collaborating with stakeholders, enhancing cloud resources, and embracing technology and innovation to improve data architecture and integration solutions.

Responsibilities

• Lead the design and execution of data architecture strategies that support business objectives
• Mentor and guide team members to deliver exceptional solutions
• Utilize team strengths to manage performance and fulfill client requirements
• Collaborate with stakeholders to enhance cloud resources effectively
• Drive innovation and technology adoption to advance data integration solutions
• Foster a culture of continuous improvement and learning within the team
• Uphold the firm's ethical standards and business conduct
• Implement strategic planning to achieve project success and quality outcomes

What You Must Have

• Bachelor's Degree in Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics
• 5 years of experience

What Sets You Apart

• Certification in Cloud Platforms [e.g., AWS Certified Solutions Architect, AWS Data Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Certified: Azure Solutions Architect Expert, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus
• Proficient in Python and SQL
• Experience with Docker and containerized deployments
• Skilled in AI techniques enhancing LLMs
• Experience in prompt engineering for LLM optimization
• Implementing data integration solutions using AWS, Azure, GCP
• Utilizing AWS CloudFormation, Azure Resource Manager, Terraform
• Building and deploying DevOps pipelines with cloud services
• Enhancing cloud resources for cost and performance