CTandI - Software And Product Innovation - Data Engineering - Senior Associate

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.

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.

Skills

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 Firms code of conduct, and independence requirements.
  
  

The Opportunity

When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills.

As part of the Data Engineering team you will design and implement scalable data solutions that enhance operational productivity. As a Senior Associate you will navigate complex data workflows, mentor junior engineers, and uphold technical standards while driving innovation within the team. This role presents a unique opportunity to work with advanced technologies and contribute to the modernization of data processes.

Responsibilities

• Design and implement scalable data solutions to improve operational productivity
• Navigate intricate data workflows and enhance processes
• Mentor junior engineers to develop their technical capabilities
• Uphold elevated standards of technical excellence in project execution
• Drive innovation within the Data Engineering team
• Collaborate with stakeholders to understand data needs
• Analyze and interpret data to inform engineering solutions
• Contribute to the modernization of data processes using advanced technologies
  
  

What You Must Have

• Bachelors Degree
• 4 years of experience
• Oral and written proficiency in English required
  
  

What Sets You Apart

• 4+ years of experience
• Migration of legacy ETL workflows to Databricks
• Designing framework-driven ETL/ELT pipelines using Python, PySpark, Spark SQL, and SQL.
• Experience with Azure data stack (ADF, Databricks, Synapse, ADLS).
• Ability to work with relational databases (PostgreSQL/SQL Server) and basic NoSQL knowledge (e.g., MongoDB).
• Familiarity with Git workflows, CI/CD, and writing clean, maintainable code.
• Developing complex data transformation workflows
• Collaborating with cross-functional engineering teams
• Designing SQL Server data ecosystems
• Monitoring and enhancing data workflows
• Applying automated orchestration frameworks

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