Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Operations

Management Level

Senior Associate

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.

*Why PWCAt PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us.At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. "

We are seeking a talented and experienced GCP Data Engineer to design, build, and maintain scalable and reliable data pipelines and infrastructure on the Google Cloud Platform. In this role, you will be crucial in transforming raw data into actionable insights, enabling data-driven decision-making across the organization by working closely with data scientists, analysts, and other stakeholders.

Responsibilities:

· Design and Development: Design, build, and maintain robust, scalable ETL/ELT data pipelines and data architectures on GCP.

· Data Processing: Implement batch and real-time data processing solutions using GCP-native services such as BigQuery, Dataflow, Dataproc, and Pub/Sub.

· Data Storage and Management: Select, manage, and optimize appropriate data storage solutions (e.g., Cloud Storage, BigQuery, Cloud SQL, Bigtable) based on performance, scalability, and cost.

· Data Quality and Governance: Implement best practices for data quality, integrity, and security across all data systems, ensuring compliance with relevant regulations (e.g., GDPR, HIPAA).

· Performance Optimization: Monitor and tune data systems and queries for optimal performance, cost-efficiency, and reliability.

· Automation and Monitoring: Automate data workflows and processes using tools like Cloud Composer (Apache Airflow) and leverage Cloud Monitoring/Logging for troubleshooting and operational efficiency.

· Collaboration: Partner with data scientists to operationalize machine learning models and collaborate with business analysts to understand data requirements and deliver tailored solutions.

· Documentation: Create and maintain clear documentation for data architectures, pipelines, and processes.

GCP Data Engineer Roles and Responsibilities in 2025

Dec 1, 2023 — GCP Data Engineer Roles and Responsibilities. A GCP Data Engineer is responsible for GCP Data Engineer roles and respon...

GCP Masters

Data Engineer - GCP Job Description Template - Expertia AI

Data Engineer - GCP Job Description Template. As a Data Engineer specializing in GCP, you will be responsible for designing, devel...

Required Qualifications and Skills

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

· Experience: Proven experience (typically 3+ years) as a Data Engineer, with a strong focus on Google Cloud Platform (GCP).

· Technical Skills:

o Proficiency in programming languages, particularly Python and SQL.

o Hands-on experience with core GCP data services: BigQuery, Dataflow, Pub/Sub, and Cloud Storage.

o Strong understanding of data warehousing concepts, data modeling (e.g., schema design, dimensional modeling), and ETL/ELT processes. o Familiarity with big data processing frameworks like Apache Spark or Apache Beam.

o Experience with version control tools like Git and CI/CD pipelines.

· Soft Skills:

o Excellent problem-solving and analytical abilities with keen attention to detail.

o Strong communication and collaboration skills to work effectively with cross-functional teams.

· Design, develop, and maintain high performance ETL/ELT pipelines using Pyspark, Python, SQL and DBT

· Build & optimize distributed data processing workflows on cloud platforms (GCP or Azure)

· Develop and maintain batch and real-time ingestion including integration with Kafka

· Ensure Data Quality and metadata management across data pipelines

· Monitor and tune data systems and queries for optimal performance, cost-efficiency, and reliability.

· Automate data workflows and processes using tools like Cloud Composer (Apache Airflow) and leverage Cloud Monitoring/Logging for troubleshooting and operational efficiency.

• Data engineering with 4-8 years of experience with strong proficiency in PySpark, Python, SQL. • Hands-on experience with GCP especially on the services like BigQuery, DataProc, Cloud Storage, Composer, Dataflow • Strong understanding of data warehousing concepts, data modelling & ETL/ELT processes with expertise in Datawarehouse / Datalake / lakehouse architecture • Familiarity with big data processing frameworks like Apache Spark and should have experience in

Apache Kafka • Experience with version control tools like Git and CI/CD pipelines.

Data engineering with 4–8 years of experience with strong proficiency in PySpark, Python, SQL, and DBT

Hands-on experience with GCP services such as BigQuery, DataProc, Cloud Storage,

Mandatory skill sets:

· Strong proficiency in SQL, Python, and PySpark. · Expertise in AWS data ecosystem – including Glue, Redshift, S3, Lambda, EMR, and Athena.

Preferred skill sets:

· AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect.

Years of experience required:

7-11

Education qualification:

B.Tech / M.Tech / MBA / MCA

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required: Bachelor of Engineering, Master of Business Administration

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Structured Query Language (SQL)

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date