GCP Data Engineer - Manager

Industry/Sector

Technology

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & Summary

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.

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.

Minimum Degree Required Bachelor's DegreeRequired Field(s) of StudyManagement Information Systems,Computer and Information Science,Systems Engineering,Electrical Engineering,Chemical Engineering,Industrial Engineering,Mathematics,Statistics,Mathematical StatisticsMinimum Year(s) of Experience5 year(s)Certification(s) Required

• GCP Professional Cloud Architect, GCP Data Engineer 
• QuickBase App Builder Certification and/ or QuickBase Expert Builder Certification 

Preferred QualificationsCertification(s) Preferred

Snowflake Core, Snowflake Architect, Databricks Data Engineer Associate 

Preferred Knowledge/Skills

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

• Design and implement comprehensive data architecture strategies that meet current and future business needs using Google Cloud services; 
• Develop and document data models, data flow diagrams, and data architecture guidelines; 
• Ensure data architecture is compliant with data governance and data security policies; 
• Collaborate with business stakeholders to understand their data requirements and translate them into technical solutions leveraging Google Cloud and Google eco-system solutions; 
• Evaluate and recommend new data technologies and tools to enhance data architecture; 
• Evaluate data and technology architecture options and build case for change across architecture principles like Security, Reliability, Scalability, Maintainability, Automation and Cost management; 
• Develop leading practices and perspectives for Data Engineering, Data Science, and Data Governance and Data Management; 
• Lead 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; 
• Architect, design, build and optimize ETL/ELT pipelines for data ingestion, processing, and storage; 
• Develop and deploy scalable data storage solutions using GCP services;  
• Architect, design, and implement scalable data pipelines and workflows using GCP tools like Dataflow, Dataprep, Data Fusion, BigQuery, and Cloud Composer,