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Posted May 2, 2026
In this role as an Associate at PwC, you will be part of the data and analytics engineering team focusing on leveraging advanced technologies to design and develop robust data solutions for clients. Your primary responsibility will involve transforming raw data into actionable insights, thereby enabling informed decision-making and driving business growth. Specifically, in data engineering at PwC, you will concentrate on designing and building data infrastructure and systems to facilitate efficient data processing and analysis. Your tasks will include developing and implementing data pipelines, data integration, and data transformation solutions. Key Responsibilities:
Analyze current business practices, processes, and procedures to identify future business opportunities for leveraging Microsoft Azure Data & Analytics Services. - Provide technical and thought leadership in areas such as data access, data processing, data integration, data modeling, database design, data visualization, and advanced analytics. - Collaborate with customers to understand business requirements and translate them into detailed technical specifications. - Develop best practices, reusable code, libraries, patterns, and frameworks for cloud-based data warehousing and ETL. - Design and implement highly performant data pipelines using Apache Spark and/or Azure Databricks. - Integrate end-to-end data pipelines to ensure data quality and consistency from source systems to target data repositories. - Evaluate the performance and applicability of multiple tools against customer requirements. - Work within an Agile delivery/DevOps methodology to deliver proof of concept and production implementation. - Integrate Databricks with other technologies such as ingestion tools and visualization tools. - Design and build data pipelines using API ingestion and Streaming ingestion methods. - Collaborate with the project team to support the delivery of additional project components. - Maintain best practice standards for cloud-based data warehouse solutioning. Qualifications Required:
3-7 years of experience as a data engineer. - BE, B.Tech, MCA, M.Tech education qualifications. - Proven experience with the spark framework (python and/or Scala) and Data Warehousing concepts. - Hands-on experience with Azure Data Factory, Apache Spark, Azure Storage, Azure SQL Data Warehouse, Azure Data Lake, Azure Cosmos DB, Azure Stream Analytics. - Expertise in Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service. - Knowledge of DevOps processes, CI/CD, and Infrastructure as code. - Understanding of Azure Cloud Infrastructure offerings and common data warehouse modeling principles. - Working knowledge of Python is desirable. - Experience in developing security models. - Databricks & Azure Big Data Architecture Certification would be a plus. - Strong collaboration, prioritization, and adaptability skills. At PwC, you will be part of a purpose-led and values-driven community that rewards your contributions, supports your well-being, and offers inclusive benefits. The environment encourages innovation and technology-driven work, enabling you to make a tangible impact in the real world. PwC is committed to providing equal employment opportunities with zero tolerance for discrimination and harassment based on various considerations. In this role as an Associate at PwC, you will be part of the data and analytics engineering team focusing on leveraging advanced technologies to design and develop robust data solutions for clients. Your primary responsibility will involve transforming raw data into actionable insights, thereby enabling informed decision-making and driving business growth. Specifically, in data engineering at PwC, you will concentrate on designing and building data infrastructure and systems to facilitate efficient data processing and analysis. Your tasks will include developing and implementing data pipelines, data integration, and data transformation solutions. Key Responsibilities:
Analyze current business practices, processes, and procedures to identify future business opportunities for leveraging Microsoft Azure Data & Analytics Services. - Provide technical and thought leadership in areas such as data access, data processing, data integration, data modeling, database design, data visualization, and advanced analytics. - Collaborate with customers to understand business requirements and translate them into detailed technical specifications. - Develop best practices, reusable code, libraries, patterns, and frameworks for cloud-based data warehousing and ETL. - Design and implement highly performant data pipelines using Apache Spark and/or Azure Databricks. - Integrate end-to-end data pipelines to ensure data quality and consistency from source systems to target data repositories. - Evaluate the performance and applicability of multiple tools against customer requirements. - Work within an Agile delivery/DevOps met
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