Google Cloud Platform Lead Data Consultant, Senior Manager

At PwC, data and analytics engineers design and develop robust data solutions, transforming raw data into actionable insights for informed decision-making and business growth. This role focuses on designing and building data infrastructure and systems, developing and implementing data pipelines, data integration, and data transformation solutions. As a strategic advisor, you will leverage expertise to deliver quality results, motivate and coach teams, and solve complex problems with sound judgment.

Must Have

• Craft and convey clear, impactful, and engaging messages.
• Apply systems thinking to identify underlying problems.
• Validate outcomes with clients and act on feedback.
• Direct the team through complex and ambiguous situations.
• Deepen and evolve your expertise to stay relevant.
• Initiate open and honest coaching conversations.
• Make difficult decisions to resolve issues hindering team effectiveness.
• Model and reinforce professional and technical standards.
• Design and implement comprehensive data architecture strategies using Google Cloud.
• Develop and document data models, data flow diagrams, and architecture guidelines.
• Assess data architecture compliance with data governance and security policies.
• Collaborate with business stakeholders to translate data requirements into technical solutions.
• Evaluate and recommend new data technologies and tools.
• Lead the implementation of GCP based solutions, ensuring best practices.
• Architect, design, build, and optimize ETL/ELT pipelines.
• Develop and deploy scalable data storage solutions using GCP services.
• Implement scalable data pipelines with GCP tools like Dataflow, BigQuery, Cloud Composer.
• Architect and implement data warehouses and data lakes.
• Develop frameworks for monitoring and troubleshooting data pipelines.
• Architect and oversee implementation of IAM roles and policies within GCP.
• Develop automation strategies leveraging Terraform for IaC deployments.
• Architect and implement services using GCP DevOps pipelines.

Perks & Benefits

• Competitive compensation package
• Inclusive benefits
• Flexibility programs
• Continuous development environment

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.

Growing as a strategic advisor, you leverage your influence, expertise, and network to deliver quality results. You motivate and coach others, coming together to solve complex problems. As you increase in autonomy, you apply sound judgment, recognising when to take action and when to escalate. You are expected to solve through complexity, ask thoughtful questions, and clearly communicate how things fit together. Your ability to develop and sustain high performing, diverse, and inclusive teams, and your commitment to excellence, contributes to the success of our Firm.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Craft and convey clear, impactful and engaging messages that tell a holistic story.
• Apply systems thinking to identify underlying problems and/or opportunities.
• Validate outcomes with clients, share alternative perspectives, and act on client feedback.
• Direct the team through complexity, demonstrating composure through ambiguous, challenging and uncertain situations.
• Deepen and evolve your expertise with a focus on staying relevant.
• Initiate open and honest coaching conversations at all levels.
• Make difficult decisions and take action to resolve issues hindering team effectiveness.
• Model and reinforce professional and technical standards, the Firm's code of conduct, and independence requirements.

Demonstrates in-depth abilities and/or success in one or many of the following areas:

• Designing and implementing comprehensive data architecture strategies that meet current and future business needs using Google Cloud services;
• Developing and documenting data models, data flow diagrams, and data architecture guidelines;
• Assessing that data architecture is compliant with data governance and data security policies;
• Collaborating with business stakeholders to understand their data requirements and translate them into technical solutions leveraging Google Cloud and Google eco-system solutions;
• Evaluating and recommending new data technologies and tools to enhance data architecture;
• Evaluating data and technology architecture options and build case for change across architecture principles like Security, Reliability, Scalability, Maintainability, Automation and Cost management;
• Developing leading practices and perspectives for Data Engineering, Data Science, and Data Governance and Data Management;
• Leading the implementation of GCP based solutions, ensuring they meet the specified requirements and best practices across batch, real-time, structured, semi-structured and unstructured datasets;
• Architecting, designing, building and optimizing ETL/ELT pipelines for data ingestion, processing, and storage;
• Developing and deploying scalable data storage solutions using GCP services;
• Architecting, designing, and implementing scalable data pipelines and workflows using GCP tools like Dataflow, Dataprep, Data Fusion, BigQuery, and Cloud Composer, ensuring robust data integration, transformation, and analytics capabilities with advanced BI platforms such as Looker and/ or Tableau;
• Architecting, designing and implementing data warehouses and data lakes, ensuring data is organized and accessible;
• Developing frameworks for monitoring and troubleshooting data pipelines, data warehouses and workflows to ensure data quality, system reliability, performance and cost management;
• Architecting and overseeing implementation of IAM roles and policies to manage access and permissions within GCP;
• Developing automation strategies leveraging Terraform for infrastructure as code (IaC) deployments;
• Architecting and implementing services using GCP DevOps services to build and deploy DevOps pipelines;
• Preferred Certification(s): GCP Data Engineer,