Data Engineer, Senior Associate

PricewaterhouseCoopers

Key Responsibilities

• Design, develop, and maintain end-to-end data pipelines across structured, semi-structured, and unstructured data sources.
• Implement data ingestion, transformation, and orchestration frameworks leveraging Azure Data Factory, Synapse, and/or Microsoft Fabric Data Pipelines.
• Develop and optimize ETL/ELT processes using Databricks (PySpark, SQL, Delta Lake) to ensure high performance and scalability.
• Implement and enforce data quality, lineage, and governance practices.
• Work closely with solution architects to design modern data architectures and ensure compliance with security and privacy standards.
• Participate in client workshops and technical discussions to translate business needs into technical designs.

Required Skills & Experience

• 3 6 years of experience in data engineering, preferably in a consulting or enterprise environment.
• Strong hands-on experience with:
  • Azure Data Platform: Data Factory, Synapse Analytics, Azure Data Lake Storage, Microsoft Fabric, Event Hub/IoT Hub, and Azure Functions.
  • Databricks: PySpark, Spark SQL, Delta Lake, Unity Catalog, and Databricks Workflows.
• Proficiency in Python and SQL for large-scale data processing and transformation.
• Solid understanding of data modeling, medallion architecture, and lakehouse principles.
• Familiarity with CI/CD pipelines, DevOps, and version control (e.g., Git, Azure DevOps).
• Knowledge of data governance, lineage, and observability tools.
• Experience with performance optimization, cost control, and best practices in cloud environments.