Assurance-Data & Analytics-Data Engineer-Senior Associate

Industry/Sector Not Applicable Specialism Assurance Management Level Senior Associate 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. Those in data and automation at PwC will focus on automating data internally using automation tools or software to streamline data-related processes within the organisation. Your work will involve automating data collection, data analysis, data visualisation, or any other tasks that involve handling and processing data.

Responsibilities

• Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others.
• Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths.
• You are expected to anticipate the needs of your teams and clients, and to deliver quality.
• Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.
• Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
• Use critical thinking to break down complex concepts.
• Use reflection to develop self awareness, enhance strengths and address development areas.
• Interpret data to inform insights and recommendations.
• 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.
•  Lead the development, optimization, and maintenance of complex data pipelines to handle large-scale data integration and transformation.  Apply advanced SQL and Python to design, build, and optimize data processing systems and workflows.  Utilize strong data modeling skills to develop and implement eƯicient and scalable database structures.  Ensure data quality, accuracy, and security throughout all stages of data processing.
•  Work extensively with cloud platforms (e.g., AWS, Azure, Google Cloud) to design and deploy scalable data solutions.  Implement cloud-based data lakes, warehouses, and other data storage solutions in collaboration with data architects and cloud engineers.  Automate and optimize cloud infrastructure to enhance performance and reduce costs.
•  Support data scientists and machine learning engineers by preparing data for machine learning and AI models.  Utilize basic knowledge of machine learning concepts to identify opportunities for predictive analytics and automation within data workflows.
•  Provide clean, structured data to business stakeholders for use in visualizations with Power BI, Tableau, QuickSight, and other tools.  Collaborate with analysts and business users to deliver data that meets their reporting and analytics needs.
•  Mentor junior data engineers and provide technical leadership in designing data solutions.  Work closely with cross-functional teams including data scientists, cloud architects, and business analysts to ensure data strategies align with business objectives.  Troubleshoot, optimize, and resolve issues in existing data infrastructure and pipelines.

Requirements

• Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Respond effectively to the diverse perspectives, needs, and feelings of others.
• Understand the broader objectives of your project or role and how your work fits into the overall strategy.
• Develop a deeper understanding of the business context and how it is changing.
•  4+ years of Experience in data engineering, with strong expertise in Python and SQL.  Extensive Experience with data modeling and designing scalable data solutions.  Proficiency with cloud platforms (e.g., AWS, Azure, Google Cloud) and cloud-native services.  Basic understanding of machine learning and AI principles, with an ability to support related initiatives.  Hands-on Experience with data visualization tools such as Power BI, Tableau, or QuickSight.  Strong problem-solving and analytical skills, with attention to detail and performance optimization.
•  Bachelor’s or Master’s degree in Computer Science, Data Science, Information Technology, or related fields.  Demonstrated Experience in building and optimizing data pipelines in cloud environments.  Ability to lead technical discussions and mentor junior team members.  Strong communication skills and Experience collaborating with cross-functional teams.
• Travel Requirements Job Posting End Date