Not Applicable
Specialism
Data, Analytics & AI
Management Level
Senior Associate
& 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 decisionmaking 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 purposeled and valuesdriven 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 .
& Summary Design and implement data solutions and data models using Azure Data Lake to support Data Warehouse, Data Lake, and Lakehouse architectures, ensuring seamless integration with Azure Fabric services. Develop and manage data ingestion pipelines for both batch and streaming data using Azure Data Fabric to ensure efficient and reliable data flow.
Responsibilities
Experience with Apache Spark / PySpark for data processing and optimization, within Azure Fabric environments. Apply data governance best practices using Azure Purview, including metadata management, data cataloging, and lineage tracking, to ensure compliance and effective data management within Azure Fabric ecosystems. Utilize Azure Fabrics Toolbox and MetadataDriven Ingestion & Processing accelerators to enhance data processing workflows and improve efficiency.
Mandatory skill sets
Perform data migration from legacy databases or other cloud platforms to Azure Fabric, leveraging Azure Migrate and other Azurenative migration tools. Collaborate with source system owners to integrate data from multiple source databases, making use of Azure Fabrics data integration capabilities to ensure seamless data consolidation.
Preferred skill sets
3+ years of experience in data engineering, with handson experience in Azure Fabric. Good understanding of Lakehouse architecture, OneLake, and Microsoft Fabric components. Strong expertise in Spark/PySpark, and Azure SQLbased solutions,Azure Data Factory, Azure Databricks. Strong experience in data migration strategies involving legacy or cloudnative data sources.
Years of experience required
5 to 10 years experience req.
Education qualification
B.Tech / M.Tech (Computer Science, Mathematics & Scientific Computing etc.)
Education
Degrees/Field of Study required Master of Engineering, Bachelor of Engineering
Degrees/Field of Study preferred
Required Skills
Fabric Design
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}
No