IN_Senior Associate_Azure Data EngineXer with Microsoft Fabric Analytics Engineer_GCC_Advisory_Bangalore

Advisory

Not Applicable

Data, Analytics & AI

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.

*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 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: 

 

Position: Azure Data Engineer / Microsoft Fabric Analytics Engineer  

Experience: 5+ Years  

Location: Bangalore  

Type: Full Time  

Certifications: Azure Data Engineer Associate (DP-203),  

Microsoft Fabric Analytics Engineer Associate (DP-600 / DP-700) – Preferred 

 

About the Role: 

We are seeking an experienced Azure Data Engineer / Microsoft Fabric Analytics Engineer to join our data engineering team. The ideal candidate will have a strong background in designing, building, and maintaining scalable data solutions using Azure Data Services and Microsoft Fabric. You will work closely with cross-functional teams to deliver high-quality data platforms that drive business insights and decision-making. 

Key Responsibilities: 

• Design, develop, and maintain end-to-end data pipelines and data integration solutions using Azure Data Factory and Microsoft Fabric. 

• Build and optimize Lakehouse and Data Warehouse solutions within Microsoft Fabric. 

• Develop data transformation logic using PySpark, Spark SQL, and Python. 

• Implement medallion architecture (Bronze, Silver, Gold) for data lake solutions. 

• Create and manage data models, semantic models, and datasets for reporting and analytics. 

• Ensure data quality, consistency, and security across all data platforms. 

• Monitor, troubleshoot, and optimize data pipeline performance. 

• Collaborate with data architects, data scientists, analysts, and business stakeholders to understand data requirements. 

• Implement data governance policies and best practices. 

• Document technical designs, data flows, and solution architectures. 

• Stay updated with the latest Azure and Microsoft Fabric features and best practices. 

 

Mandatory skill sets: 

 

Required Skills: 

• 5+ years of hands-on experience in data engineering and analytics. 

• Proficiency in Azure Data Services including: 

• Azure Data Factory 

• Azure Synapse Analytics 

• Azure Data Lake Storage (ADLS Gen2) 

• Azure SQL Database 

• Proficiency in Microsoft Fabric workloads: 

• Data Engineering (Lakehouse, Notebooks) 

• Data Warehouse 

• Data Pipelines 

• OneLake 

• Strong programming skills in PySpark, Spark SQL, Python, and SQL. 

• Experience with data modeling (dimensional modeling, star/snowflake schemas). 

• Knowledge of ETL/ELT design patterns and best practices. 

• Experience with Delta Lake and lakehouse architecture. 

• Strong analytical, problem-solving, and troubleshooting skills. 

• Excellent communication and collaboration skills. 

 

 

Preferred skill sets: 

 

• Microsoft Certified: Azure Data Engineer Associate (DP-203). 

• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600). 

• Experience with Databricks and Delta Lake. 

• Experience with Power BI for data visualization and reporting. 

• Knowledge of CI/CD pipelines for data engineering (Azure DevOps, Git). 

• Experience working in Agile/Scrum environments. 

• Exposure to data quality frameworks and tools. 

 

Years of experience required: 

 

Experience  

• 5+ years 

Education qualification: 

 

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

Mobile Device Management (MDM)

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, AI Fluency, AI-Human Collaboration, 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 {자세히(30)}

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May 18, 2026