IN_Manager 2_Azure Data Engineer_OC-Data & Analytics_Advisory_Bhubaneswar

Advisory

Not Applicable

Data, Analytics & AI

Manager

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: We are seeking a highly skilled and visionary Senior Manager – Data Science & AI to lead our advanced analytics and AI/ML initiatives, including next-generation technologies like Generative AI and Agentic AI. The ideal candidate will be responsible for managing data science teams, driving innovation in machine learning model development, and operationalizing AI solutions that deliver measurable business value.

Job Description & Summary: A career within…. 

 

Responsibilities: 

 

 

Design and implement end-to-end data pipelines using ADF, ADB, and Microsoft Fabric. 

Develop scalable ETL/ELT processes using PySpark and Databricks Notebooks. 

Integrate data from various sources including on-premise and cloud-based systems. 

Optimize data workflows for performance, scalability, and reliability. 

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

Monitor, troubleshoot, and enhance existing data pipelines and workflows. 

Implement data governance, security, and compliance best practices. 

Work in Agile/Scrum environments and participate in sprint planning and reviews. 

 

Mandatory skill sets: 

 

Azure Data Factory (ADF), Azure Databricks (ADB), Microsoft Fabric (Data Engineering & Data Factory experiences), PySpark and Spark SQL, Proficiency in SQL, Python, and data modeling, Experience with Delta Lake, Lakehouse architecture, and data lakes. 

Preferred skill sets: 

 

Azure Synapse Pipelines, Azure Stream Analytics, Azure Event Hubs and IoT Hub, Microsoft Purview (governance, lineage, catalog), Familiarity with CI/CD pipelines and DevOps practices in Azure, Understanding of data security, RBAC, and data lineage. Azure certification is a plus. 

Years of experience required: 

 

8 to 15 years 

Education qualification: 

 

Graduate Engineer or Management Graduate 

Data Engineering

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, 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 {+ 36 more}

Not Specified

No

No

July 7, 2026