Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI 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 PWC At 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. " Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. 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. Mandatory skill set s: Python, SQL, BigQuery , Dataflow, Pub/Sub, and Cloud Storage Preferred skill sets : Data proc, Apache Spark Years of experience required : 4 - 8 yrs Education qualification : B.Tech / M.Tech / M.E / MCA/ B.E Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Master of Engineering, Master of Business Administration, Bachelor of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills PySpark 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 lang