Industry/Sector
Not ApplicableSpecialism
Product InnovationManagement Level
Senior AssociateJob 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.
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:
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:
Communication & Collaboration:
Preferred Skills:
The Opportunity
Responsibilities
What You Must Have
What Sets You Apart
Travel Requirements
Not SpecifiedJob Posting End Date