IN-Manager_ Azure DE + GCP _Data and Analytics_Advisory_Bangalore

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

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, develop, and maintain scalable data pipelines using Python, PySpark, and Spark (Scala/PySpark) across Azure and GCP platforms. 

• Build and manage data workflows using Databricks Workflows and Apache Airflow / Cloud Composer DAGs. 

• Develop and optimize Delta Lake tables on Databricks, ensuring data reliability, performance, and governance. 

• Implement and manage Databricks Unity Catalog for data access control and metadata management. 

• Work with BigQuery for large-scale data warehousing and analytics. 

• Develop event-driven and batch data processing solutions using Pub/Sub, Cloud Dataflow, and Cloud Functions. 

• Implement ML pipelines on Databricks, including experimentation tracking using MLflow. 

• Collaborate with data scientists, analytics teams, and business stakeholders to deliver end-to-end data solutions. 

• Ensure best practices for data quality, security, cost optimization, and performance tuning. 

• Support CI/CD pipelines and production deployments for data engineering workloads. 

Mandatory skill sets: 

• Azure Databricks 

• Python, PySpark 

• Advanced Spark (PySpark / Scala) 

• Databricks Delta Tables 

• Databricks Workflows 

• Unity Catalog 

• Apache Airflow / Cloud Composer DAGs 

• BigQuery 

• GCP Native Services: 

• BigQuery 

• Cloud Composer 

• Cloud Functions 

• Pub/Sub 

Preferred skill sets: 

• Machine Learning on Databricks 

• MLflow for experiment tracking and model lifecycle management 

• Google Cloud Dataflow 

• Cloud Data Fusion 

• Experience with event-driven architecture 

• Exposure to multi-cloud (Azure + GCP) data platforms 

• Knowledge of data governance, security, and compliance best practices 

Years of experience required: 

6 to 10+ Years 

Education qualification: 

BE, B.Tech, ME, M,Tech, MBA, MCA (60% above) 

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

Degrees/Field of Study required: Master Degree, Bachelor of Engineering

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

GCP Dataflow

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, 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 {+ 32 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

May 14, 2026