Assurance-Data & Analytics-Data Engineer-Senior Associate

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.

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.

Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.

Use critical thinking to break down complex concepts.

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.

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.

Key Responsibilities:

Data Engineering & Modeling:

 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.

Cloud Data Solutions:

 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.

Machine Learning & AI Support:

 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.

Data Visualization:

 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.

Collaboration & Leadership:

 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.

Required Skills and Experience:

 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.

Qualifications:

 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.