Data Engeerg - Experienced 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 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.

• Design, develop, and maintain robust, scalable ETL pipelines using tools like Apache Spark, Kafka, and other big data technologies.
• Ingest, process, and store structured, semistructured, and unstructured data from various sources.
• Demonstrate proficiency in Python, PySpark, Spark, and a solid understanding of design patterns (eg, SOLID).
• Optimize ETL processes to ensure scalability and efficiency.
• Work with various file formats, such as JSON, CSV, Parquet, and Avro.
• Should have intermediate level knowledge of RDBMS, NoSQL databases, and CAP theorem principles
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and optimize data models for performance and scalability.
• Document data processes, architectures, and models comprehensively to facilitate crossteam understanding and maintenance.
• Implement and maintain CI/CD pipelines using tools like Docker, Kubernetes, and GitHub.
• Ensure data quality, integrity, and security across all systems and processes.
• Implement and monitor data governance best practices.
• Stay uptodate with emerging data technologies and trends, and identify opportunities for innovation and improvement.
• Knowledge of other Cloud Data/Integration/Orchestration Platforms Snowflake, Databricks, Azure Data Factory etc is good to have