📍 Job Overview

Job Title: Google Cloud Data Architect
Company: PwC
Location: Warsaw, Mazowieckie, Poland
Job Type: Hybrid
Category: Data Architecture
Date Posted: 2025-05-27
Experience Level: 5-10 years
Remote Status: On-site/Hybrid

🚀 Role Summary

Design and implement complex data architecture projects on Google Cloud Platform (GCP), focusing on business requirements, scalability, performance, security, and cost optimization.
Collaborate with client teams to understand their needs and deliver optimal solutions.
Ensure data security and compliance with relevant regulations, such as RODO.
Document technical aspects of designed and implemented solutions.
Share knowledge and support other team members in developing GCP-related skills.
Implement Infrastructure as Code and plan/migrate data to GCP.
Develop multi-cloud and AI solutions.

📝 Enhancement Note: This role requires a strong background in data architecture and GCP services, with a focus on data processing, transformation, and storage. Familiarity with multi-cloud environments and AI integration is a plus.

💻 Primary Responsibilities

Architecture Design: Design and implement data architecture projects on GCP, considering business requirements, scalability, performance, security, and cost optimization.
Solution Implementation: Implement solutions using various GCP services, such as BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer/Airflow, and Cloud Functions.
Data Pipeline Design: Design and implement reliable and efficient data pipelines for data processing, transformation, and loading (ETL/ELT).
Performance Optimization: Monitor, analyze, and optimize the performance of existing data solutions in GCP, identifying bottlenecks and implementing improvements.
Cost Control: Control and optimize costs associated with GCP service usage.
Security & Compliance: Ensure data security and compliance with relevant regulations, such as RODO.
Documentation: Create and maintain up-to-date technical documentation for designed and implemented solutions.
Knowledge Sharing: Share knowledge and support other team members in developing GCP-related skills.
Infrastructure as Code: Implement solutions in the form of Infrastructure as Code.
Data Migration: Plan and execute data migrations to GCP.
Multi-cloud & AI Solutions: Develop multi-cloud and AI solutions.

📝 Enhancement Note: This role requires a strong understanding of data architecture principles and GCP services. Experience with multi-cloud environments and AI integration will be beneficial for this role.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Information Technology, or a related field.

Experience: At least 5 years of experience in data solutions design and implementation, with a minimum of 2 years on Google Cloud Platform.

Required Skills:

Proficient in SQL and at least one programming language: Python, Java, Scala.
Experience in data warehouse and data lake design.
Strong knowledge of GCP services, including BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer/Airflow, and Cloud Functions.
Experience with data processing, transformation, and storage.
Familiarity with data security and compliance regulations.
Problem-solving skills and proactivity.
Experience with Infrastructure as Code tools (e.g., Terraform).
Ability to communicate effectively with client teams in Polish and English (minimum B2).
Experience with CI/CD tools (e.g., Jenkins, GitLab CI).

Preferred Skills:

Knowledge of data solutions in other public clouds, such as Microsoft Azure or Amazon Web Services.
Google Cloud Professional Data Engineer or Professional Cloud Architect certification.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate experience in data architecture design and implementation on GCP.
Showcase projects that highlight data processing, transformation, and storage solutions.
Include examples of multi-cloud and AI integration, if applicable.

Technical Documentation:

Provide well-structured and clear documentation for your data architecture projects.
Include data flow diagrams, database schemas, and any relevant code snippets.
Explain the reasoning behind architectural decisions and any performance optimizations.

📝 Enhancement Note: A strong portfolio will showcase the candidate's ability to design and implement complex data architecture projects on GCP, with a focus on performance, scalability, and security.

💵 Compensation & Benefits

Salary Range: The estimated salary range for this role in Warsaw, Poland is between PLN 15,000 and PLN 25,000 per month, depending on experience and qualifications. This estimate is based on regional market research and industry standards for data architects with 5-10 years of experience.

Benefits:

Flexible Working Conditions: Elastyczny początek dnia, workation, sabbatical leave.
Development and Skill Enhancement: Full support from the team during the onboarding process, mentoring, training, workshops, and co-financed certifications.
Comprehensive Medical and Wellbeing Program: A wide range of medical and wellbeing benefits, including health insurance, wellness programs, and employee assistance programs.
Diverse Insurance Options: Various insurance options, such as travel insurance and legal assistance.
Coaching and Psychological Consultations: Access to coaching and psychological consultations to support employee well-being.
Concierge for Young Parents: Assistance with childcare and other family-related needs.
Sports Groups: Opportunities to participate in various sports groups and activities.
Individual Benefit Plan: The ability to create a personalized benefit plan tailored to the employee's needs.
Paid Volunteer Time: Three hours of paid leave per month for volunteer work.
Additional Day Off for Birthdays: An extra day off to celebrate birthdays.

📝 Enhancement Note: The salary range provided is an estimate based on regional market research and industry standards. The actual salary may vary depending on the candidate's experience and qualifications.

🎯 Team & Company Context

🏢 Company Culture

Industry: PwC is a global professional services network focused on providing audit, tax, and consulting services. The company operates in the professional services industry, with a strong focus on technology and digital transformation.

Company Size: PwC is a large global organization with over 284,000 employees in 157 countries. This size allows for diverse project opportunities and extensive resources for professional development.

Founded: PwC was founded in 1874 and has since grown into one of the largest professional services firms in the world. The company has a long history of innovation and adaptation to changing market conditions.

Team Structure:

The Cloud & Digital team at PwC Poland consists of experienced professionals with expertise in various aspects of cloud and digital transformation.
The team is organized into specialized sub-teams focusing on cloud strategy, migrations, data engineering, AI, DevOps, application modernization, and cloud-native development.
The team works collaboratively with other PwC teams and client teams to deliver comprehensive solutions.

Development Methodology:

PwC follows Agile methodologies for software development and project management.
The team uses version control systems, such as Git, for collaborative development and code reviews.
PwC employs CI/CD pipelines and automated deployment tools to ensure efficient and reliable software delivery.
The team uses project management tools, such as Jira, to track progress and facilitate collaboration.

Company Website: https://www.pwc.com/

📝 Enhancement Note: PwC's large size and global presence offer extensive opportunities for professional development and career growth. The company's focus on technology and digital transformation provides a dynamic and innovative work environment for data architects.

📈 Career & Growth Analysis

Data Architecture Career Level: This role is at the senior level, requiring a deep understanding of data architecture principles and extensive experience in designing and implementing complex data solutions on GCP. The role involves leading projects, mentoring junior team members, and making critical architectural decisions.

Reporting Structure: The data architect reports directly to the Cloud & Digital team manager and works collaboratively with other team members, as well as client teams.

Technical Impact: The data architect plays a crucial role in designing and implementing data solutions that drive business value, improve user experience, and support data-driven decision-making. The role requires a strong understanding of data processing, transformation, and storage, as well as data security and compliance.

Growth Opportunities:

Technical Specialization: Pursue specialized certifications, such as Google Cloud Professional Data Engineer or Professional Cloud Architect, to deepen expertise in GCP services.
Leadership Development: Develop leadership skills by mentoring junior team members and taking on more complex projects with higher stakes.
Architecture Decision-Making: Gain experience in making critical architectural decisions that impact the scalability, performance, and security of data solutions.

📝 Enhancement Note: This role offers significant opportunities for career growth and technical specialization within the data architecture field. The large and diverse client base of PwC provides exposure to various industries and projects, allowing for continuous learning and skill development.

🌐 Work Environment

Office Type: PwC's Warsaw office is a modern, collaborative workspace designed to facilitate team interaction and knowledge sharing. The office features open-plan workspaces, meeting rooms, and breakout areas.

Office Location(s): PwC's Warsaw office is located at ul. Polna 11, 00-640 Warsaw, Poland. The office is easily accessible by public transportation and offers convenient parking options.

Workspace Context:

The workspace is equipped with modern technology, including high-speed internet, multiple monitors, and testing devices, to support effective data architecture work.
The open-plan layout encourages collaboration and knowledge sharing among team members.
The office features dedicated spaces for quiet work, as well as areas for informal discussions and team-building activities.

Work Schedule: The hybrid work arrangement allows for flexible working hours, with a core working time of 10:00 AM to 3:00 PM. The team follows Agile methodologies, with regular sprint planning and stand-up meetings to ensure efficient project progress.

📝 Enhancement Note: PwC's modern and collaborative workspace provides an ideal environment for data architects to work effectively and collaborate with team members and clients.

📄 Application & Technical Interview Process

Interview Process:

Phone Screen: A brief phone conversation to assess communication skills and cultural fit.
Technical Assessment: A hands-on technical assessment focusing on data architecture design, GCP services, and data processing, transformation, and storage.
Client Team Interaction: A meeting with the client team to discuss project requirements and assess communication and collaboration skills.
Final Evaluation: A final interview to evaluate the candidate's overall fit for the role, considering technical skills, cultural fit, and career aspirations.

Portfolio Review Tips:

Highlight relevant data architecture projects on GCP, focusing on data processing, transformation, and storage.
Include examples of multi-cloud and AI integration, if applicable.
Provide clear and concise documentation for each project, explaining the data architecture design, GCP services used, and any performance optimizations implemented.
Prepare a live demo or presentation to showcase your projects and answer questions from the interview panel.

Technical Challenge Preparation:

Brush up on GCP services, including BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer/Airflow, and Cloud Functions.
Review data architecture principles and best practices for designing and implementing complex data solutions on GCP.
Practice explaining technical concepts and architectural decisions clearly and concisely.

ATS Keywords: Google Cloud Platform, Data Architecture, BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer, Airflow, Cloud Functions, SQL, Python, Java, Scala, Infrastructure as Code, CI/CD, Data Warehouse, Data Lake, Multi-cloud, AI, Data Processing, Data Transformation, Data Storage, Data Security, RODO, Agile, Hybrid Work, Collaboration, Knowledge Sharing, Mentoring, Leadership, Technical Specialization, Career Growth.

📝 Enhancement Note: The interview process for this role focuses on assessing the candidate's technical skills in data architecture and GCP services, as well as their ability to collaborate with client teams and make critical architectural decisions.

🛠 Technology Stack & Web Infrastructure

Frontend Technologies: Not applicable for this role.

Backend & Server Technologies:

Google Cloud Platform (GCP): The primary technology stack for this role, including services such as BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer/Airflow, and Cloud Functions.
SQL: Used for data manipulation, querying, and defining database schemas.
Python, Java, Scala: Programming languages used for data processing, transformation, and storage tasks, as well as for implementing Infrastructure as Code solutions.

Development & DevOps Tools:

Version Control: Git for collaborative development and code reviews.
CI/CD Pipelines: Jenkins or GitLab CI for automated testing and deployment.
Project Management: Jira for tracking project progress and facilitating collaboration.
Infrastructure as Code: Terraform for defining and provisioning cloud resources.

📝 Enhancement Note: The technology stack for this role is centered around Google Cloud Platform services, with a focus on data processing, transformation, and storage. Familiarity with GCP services, SQL, and relevant programming languages is essential for success in this role.

👥 Team Culture & Values

Data Architecture Values:

User-Centric Design: Focus on understanding and addressing user needs through data-driven insights and innovative solutions.
Performance Optimization: Continuously monitor and optimize data solutions to ensure efficient processing, transformation, and storage, as well as fast and reliable data access.
Scalability & Flexibility: Design data solutions that can scale to meet growing demands and adapt to changing business requirements.
Security & Compliance: Prioritize data security and compliance with relevant regulations, such as RODO, to protect user data and maintain trust.
Continuous Learning: Foster a culture of continuous learning and knowledge sharing to stay up-to-date with the latest data architecture trends and best practices.

Collaboration Style:

Cross-Functional Integration: Collaborate with various teams, including data engineers, software developers, and project managers, to deliver comprehensive data solutions.
Code Review Culture: Encourage peer reviews and pair programming to ensure code quality, knowledge sharing, and collective code ownership.
Knowledge Sharing: Foster a culture of knowledge sharing, mentoring, and continuous learning to support the professional development of team members.

📝 Enhancement Note: PwC's data architecture team values user-centric design, performance optimization, scalability, security, and continuous learning. The team fosters a collaborative culture that encourages knowledge sharing, mentoring, and collective code ownership.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Processing & Transformation: Design and implement efficient data processing and transformation pipelines using GCP services, such as BigQuery, Dataflow, and Dataproc.
Data Storage: Select appropriate data storage solutions, such as Cloud Storage and BigQuery, based on data access patterns, scalability, and cost optimization requirements.
Performance Optimization: Continuously monitor and optimize data solutions to ensure fast and reliable data access, efficient resource utilization, and cost control.
Multi-cloud & AI Integration: Design and implement data solutions that integrate with other cloud platforms, such as Microsoft Azure or Amazon Web Services, and leverage AI services for data analysis and prediction.

Learning & Development Opportunities:

Technical Skill Development: Pursue specialized certifications, such as Google Cloud Professional Data Engineer or Professional Cloud Architect, to deepen expertise in GCP services.
Emerging Technologies: Stay up-to-date with the latest data architecture trends and best practices, and explore emerging technologies, such as AI and machine learning, to expand your skillset.
Leadership Development: Develop leadership skills by mentoring junior team members, taking on more complex projects, and contributing to the team's strategic decision-making processes.

📝 Enhancement Note: This role presents various technical challenges and learning opportunities for data architects looking to expand their skillset and advance their careers. The diverse client base of PwC provides exposure to various industries and projects, allowing for continuous learning and skill development.

💡 Interview Preparation

Technical Questions:

Data Architecture Design: Describe your approach to designing data architecture solutions on GCP, focusing on business requirements, scalability, performance, security, and cost optimization.
GCP Services: Explain your experience with GCP services, such as BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer/Airflow, and Cloud Functions, and how you have used them to design and implement data solutions.
Data Processing & Transformation: Discuss your experience with data processing, transformation, and storage, and how you have optimized data pipelines for efficiency and performance.
Data Security & Compliance: Describe your approach to ensuring data security and compliance with relevant regulations, such as RODO, in data architecture solutions.
Multi-cloud & AI Integration: Explain your experience with multi-cloud environments and AI integration, and how you have designed and implemented data solutions that leverage these technologies.

Company & Culture Questions:

PwC Culture: Describe what you understand about PwC's culture and how you can contribute to the team's success.
Client Interaction: Explain your experience working with client teams and how you approach understanding their needs and delivering optimal solutions.
Agile Methodologies: Discuss your experience with Agile methodologies and how you have applied them to data architecture projects.

Portfolio Presentation Strategy:

Project Selection: Choose relevant data architecture projects from your portfolio that demonstrate your experience with GCP services, data processing, transformation, and storage, as well as any multi-cloud and AI integration.
Storytelling: Prepare a clear and concise narrative for each project, explaining the data architecture design, GCP services used, and any performance optimizations implemented.
Live Demo: Prepare a live demo or presentation to showcase your projects and answer questions from the interview panel.

📝 Enhancement Note: The interview process for this role focuses on assessing the candidate's technical skills in data architecture and GCP services, as well as their ability to collaborate with client teams and make critical architectural decisions. The portfolio presentation strategy should highlight relevant projects and demonstrate the candidate's ability to design and implement complex data solutions on GCP.

📌 Application Steps

To apply for this Google Cloud Data Architect position at PwC:

Update Your Portfolio: Highlight relevant data architecture projects on GCP, focusing on data processing, transformation, and storage. Include examples of multi-cloud and AI integration, if applicable. Prepare clear and concise documentation for each project, explaining the data architecture design, GCP services used, and any performance optimizations implemented. Prepare a live demo or presentation to showcase your projects and answer questions from the interview panel.
Optimize Your Resume: Tailor your resume to emphasize your technical skills in data architecture and GCP services. Highlight your experience with data processing, transformation, and storage, as well as any multi-cloud and AI integration. Include relevant keywords to improve the visibility of your resume in applicant tracking systems.
Prepare for Technical Challenges: Brush up on GCP services, data architecture principles, and best practices for designing and implementing complex data solutions on GCP. Practice explaining technical concepts and architectural decisions clearly and concisely.
Research PwC: Familiarize yourself with PwC's company culture, values, and mission. Understand the company's focus on technology and digital transformation, and how this role contributes to that vision. Prepare thoughtful questions to ask during the interview process to demonstrate your interest in the company and the role.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web technology industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Google Cloud Data Architect