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 science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.
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 Firm's 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 and Analytics team you will design, build, and operate resilient systems that power our applications across multiple cloud platforms. As a Senior Associate you will analyze complex problems, mentor junior engineers, and maintain rigorous standards while maintaining the security and availability of our infrastructure.
Responsibilities
- Deploy, manage, and scale Kubernetes applications using kubectl and Helm, including performing rolling updates and rollbacks.
- Build, push, and manage Docker images through JFrog Artifactory and Azure Container Registry.
- Design, implement, and maintain YAML-driven CI/CD pipelines across Azure DevOps, GitHub Actions, and Oracle Cloud Infrastructure DevOps, integrating automated testing, security scans, and artifact promotion.
- Develop and maintain Terraform modules to provision compute, networking, and platform resources across AWS, Azure, GCP, and Oracle Cloud.
- Set up and manage monitoring, logging, and alerting systems using Datadog, Prometheus, Grafana, or ELK Stack, and define SLOs/SLAs to support incident response and root cause analysis.
- Automate infrastructure provisioning, routine maintenance, and monitoring workflows, including managing IP address assignments and DNS mappings for services.
- Utilize LLMOps tools like MLflow or LangSmith for experiment tracking and model monitoring in machine learning workflows.
What You Must Have
- Bachelor's & Master's Degree
- 4 years of experience
- Oral and written proficiency in English required
What Sets You Apart
- Preferred Master’s degree in Engineering, Computer Science, or related field, with relevant certifications like AWS Certified DevOps Engineer or Azure DevOps Engineer.
- Experience working across multi-cloud environments including AWS, Azure, GCP, or Oracle Cloud.
- Proven ability to build and manage CI/CD pipelines using tools such as GitHub Actions, Azure DevOps, or Jenkins.
- Hands-on expertise with monitoring and logging tools like Datadog, Prometheus, Grafana, or ELK Stack.
- Strong skills in container orchestration and automation of CI/CD workflows.
- Proficient in infrastructure as code (IaC) practices and scripting for automation tasks.
