GCP Data Engineer - Senior Associate

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.

Preferred Knowledge/Skills

Job Title: Google Cloud Data Engineer - Senior Associate

Role Overview: PwC US - Acceleration Center seeks a skilled Data Engineer - Senior Associate to design, build, and maintain robust data pipelines and cloud-native data platforms on Google Cloud Platform (GCP). As a core member of our delivery team, you will translate business requirements into efficient technical implementations, ensuring high-quality, scalable, and secure data solutions. You will work closely with architects and team leads to execute data strategies while applying best practices in modern data engineering and cloud-native architecture.

Responsibilities:

• Solution Implementation: Execute the design and development of data pipelines and warehousing solutions based on architectural blueprints. Convert complex business needs into clean, performant, and scalable data models.
• Data Platform Engineering: Develop and maintain high-performance data ingestion, processing, and transformation workflows within the GCP ecosystem. Implement data modeling frameworks (e.g., Star Schema, Data Vault) and apply transformation logic using dbt or Dataform.
• GCP Development: Leverage core Google Cloud data services, including BigQuery, Cloud Storage, Dataflow, and Pub/Sub. Implement cloud-native solutions using Cloud Composer (Airflow), GKE, and Cloud Run to ensure reliability and scalability.
• Orchestration & Transformation: Build and manage data orchestration workflows using Apache Airflow / Cloud Composer. Write modular, testable, and version-controlled SQL transformations using dbt to ensure data accuracy and quality.
• DataOps & Quality: Implement and maintain CI/CD pipelines, automated testing, and monitoring frameworks. Ensure high data quality, observability, and reproducible deployments through robust DataOps practices.
• Technical Collaboration: Work effectively within agile teams, participating in code reviews, mentoring junior engineers, and communicating technical blockers or progress clearly to project leadership.
• Security & Governance: Apply best practices for data security, including access control, encryption, and audit logging. Ensure all data solutions adhere to firm-wide security and compliance standards.
  
  

Requirements:

• Experience Profile:
• 4–8 years of professional experience in data engineering, software development, or big data architecture.
• 3+ years of hands-on experience building solutions on Google Cloud Platform (GCP).
• Strong background in data modeling, database design, and end-to-end data pipeline development.
• Technical Expertise:
• Python: Proficient in using Python for data processing, scripting, and building custom data pipelines.
• SQL: Advanced SQL skills for complex data analysis, query tuning, and database optimization.
• Orchestration: Proven experience building, debugging, and managing complex DAGs in Apache Airflow (Cloud Composer).
• Transformation: Hands-on experience with dbt (data build tool) for managing transformation logic and quality testing.
• Modern Data Stack: Deep understanding of ELT/ETL patterns, data warehousing (BigQuery), and data lake architectures.
• GCP Proficiency:
• Experience with BigQuery, Dataflow (Apache Beam), and Cloud Storage.
• Familiarity with containerization and infrastructure management tools (e.g., Docker, Terraform).
• Experience with CI/CD implementation and version control systems (Git).
• Communication & Collaboration:
• Strong verbal and written communication skills with the ability to explain technical details to non-technical stakeholders.
• Self-motivated, detail-oriented, and able to work collaboratively in a fast-paced, client-facing environment.
  
  

Preferred Skills:

• GCP Professional Certifications (e.g., Professional Data Engineer, Professional Cloud Architect).
• Experience in client-facing or consulting environments.
• Exposure to migrating legacy systems to modern cloud data platforms (e.g., migrations from on-prem or other clouds to GCP).
• Knowledge of data privacy regulations (GDPR, CCPA) and handling PII data within cloud environments.
  
  

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 Analytics & Insights Managed Services team you will empower companies to transform their approach to analytics and insights while building your skills in exciting new directions. As a Senior Associate, you will take ownership of complex data solutions, drive innovative practices, and mentor junior teammates across the entire data lifecycle. This position provides an opportunity to have a voice in designing, building, and operating the next generation of software and services, making a significant impact on business performance.

Responsibilities

• Take ownership of intricate data solutions
• Drive leading practices across the entire data lifecycle
• Mentor junior team members to enhance their skills
• Collaborate on the design and implementation of innovative software and services
• Contribute to improving business performance through analytics
• Engage in continuous learning and skill development
• Foster a culture of collaboration and knowledge sharing
• Analyze data to derive actionable insights
  
  

What You Must Have

• Bachelors Degree in computer science, Data Engineering, Information Systems, or a related technical field
• 5 years of hands-on experience designing, building, and operating data platforms and pipelines
• Oral and written proficiency in English required
  
  

What Sets You Apart

• Advanced skills in data pipeline development
• Experience architecting scalable ETL/ELT workflows
• Proficiency in big data and streaming ecosystems
• Knowledge of cloud and hybrid infrastructure deployment
• Skills in data modeling and warehousing
• Experience with DevOps and automation practices
• Understanding of data governance and quality assurance
• Ability to mentor and lead junior engineers

---