Senior Associate_Azure Data Engineer_Data & Analytics_Advisory

Not Applicable Data, Analytics & AI Senior Associate At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.

In business intelligence at PwC, you will focus on leveraging data and analytics to provide strategic insights and drive informed decisionmaking for clients. You will develop and implement innovative solutions to optimise business performance and enhance competitive advantage.

• Design, develop, and optimize data pipelines and ETL processes using PySpark or Scala to extract, transform, and load large volumes of structured and unstructured data from diverse sources.
• Implement data ingestion, processing, and storage solutions on Azure cloud platform, leveraging services such as Azure Databricks, Azure Data Lake Storage, and Azure Synapse Analytics.
• Develop and maintain data models, schemas, and metadata to support efficient data access, query performance, and analytics requirements.
• Monitor pipeline performance, troubleshoot issues, and optimize data processing workflows for scalability, reliability, and costeffectiveness.
• Implement data security and compliance measures to protect sensitive information and ensure regulatory compliance.
• Requirement
• Proven experience as a Data Engineer, with expertise in building and optimizing data pipelines using PySpark, Scala, and Apache Spark.
• Handson experience with cloud platforms, particularly Azure, and proficiency in Azure services such as Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database.
• Strong programming skills in Python and Scala, with experience in software development, version control, and CI/CD practices.
• Familiarity with data warehousing concepts, dimensional modeling, and relational databases (e.g., SQL Server, PostgreSQL, MySQL).
• Experience with big data technologies and frameworks (e.g., Hadoop, Hive, HBase) is a plus.

Degrees/Field of Study required Master of Business Administration, Master of Engineering, Bachelor of Engineering Degrees/Field of Study preferred PySpark Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Business Case Development, Business Data Analytics, Business Intelligence and Reporting Tools (BIRT), Business Intelligence Development Studio, Communication, Competitive Advantage, Continuous Process Improvement, Creativity, Data Analysis and Interpretation, Data Architecture, Database Management System (DBMS), Data Collection, Data Pipeline, Data Quality, Data Science, Data Visualization, Embracing Change, Emotional Regulation, Empathy, Inclusion, Industry Trend Analysis {+ 12 more}