Data Engineer

PwC is a global network of professionals providing audit, consulting, tax, and technology services. The organization delivers innovative solutions by combining expertise from across its international network to address complex business challenges.

• Design, implement, and maintain scalable data pipelines and ETL/ELT processes using Python and Spark;
• Build and manage data warehouses and data lakes, including designing star/snowflake schemas;
• Collaborate with data scientists and ML engineers to implement preprocessing and feature engineering for machine learning models;
• Optimize data processing jobs and SQL queries for performance and cost efficiency;
• Monitor production data pipelines to ensure reliability, scalability, and adherence to SLAs;
• Translate client business needs into technical designs and provide guidance on data architecture;
• Implement data quality checks, validation frameworks, and governance standards;
• Ensure data security, privacy, and compliance with internal and client requirements;
• Review code and mentor junior team members on best practices.

• Strong programming skills in Python, including pandas, PySpark, and SQLAlchemy;
• Hands-on experience building data pipelines using distributed processing frameworks like Spark;
• Proficiency in designing ETL/ELT workflows and working with large, complex datasets;
• Expertise in SQL database design, schema creation, and query optimization;
• At least 2 years of professional experience in data engineering or BI engineering;
• Strong analytical mindset for debugging and designing efficient data flows;
• English at B2 level or higher;
• Nice to have: Experience with cloud data platforms (Azure Synapse, Databricks, Data Factory, Azure SQL, Data Lake), experience with AWS or GCP, knowledge of other programming languages.

• No conditions specified