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.
Skills
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.
The OpportunityWhen 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 and Analytics Engineering team you will lead the development of innovative AI-enabled solutions that drive worth for our clients. As a Manager you will supervise and mentor teams, delivering quality outputs while cultivating meaningful client relationships and navigating complex challenges.
Responsibilities
- Lead the creation of innovative AI-driven solutions for client needs
- Supervise and mentor team members to secure quality outcomes
- Cultivate sturdy relationships with clients while addressing challenges
- Analyze complex problems and develop impactful strategies
- Foster a collaborative team environment to enhance performance
- Maintain adherence to project timelines and deliverables
- Utilize technology to improve processes and outcomes
- Drive continuous improvement initiatives within the team
What You Must Have
- Bachelor's Degree
- 7 years of experience
- Oral and written proficiency in English required
What Sets You Apart
- Bachelor's Degree in Computer and Information Science, Database Administration, Management Information Systems, Software Applications, Cloud technologies preferred
- Demonstrating knowledge of data architecture and management
- Analyzing source systems for ETL/ELT components and ingestion flows for common data formats (JSON, Parquet, CSV).
- Strong programming skills in Python (mandatory), PySpark, Spark SQL, and SQL.
- Proven experience with Azure data services (ADF, Synapse, ADLS, and Databricks).
- Experience building high-volume batch and real-time pipelines using Spark and Kafka/Event Hubs.
- Solid understanding of relational databases (PostgreSQL/SQL Server) and basic NoSQL concepts.
- Familiarity with Git-based workflows, CI/CD, and containerization (Docker).
- Building complex, scalable analytics solutions
- Creating data integration using iPaaS tools
- Understanding and implementing process design and data models
- Addressing performance and data quality issues
- Demonstrating knowledge of data visualization tools
- Documenting processes and procedures
