ETIC, Data Engineer, Senior Associate

Data Engineer

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 decision-making 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.

We're looking for a versatile Data Engineer who's equally comfortable building data pipelines as they are digging into complex SQL queries and supporting ad hoc data needs. This role straddles the line between engineering and analytics, requiring someone who thrives on solving business problems through data and has a strong grasp of relational databases, data modeling, and hands-on data manipulation. You'll play a key role in maintaining data accuracy across systems, supporting stakeholders with one-off data needs, and making targeted updates directly in production databases.

Responsibilities:

• Write SQL queries to extract, analyze, and transform data for business reporting or internal use.
• Create and execute ad hoc insert, update, and delete scripts in complex relational databases.
• Partner with analysts, product managers, and business stakeholders to fulfill one-off data requests and generate insights.
• Ensure data integrity and accuracy when performing manual interventions or debugging data issues.
• Collaborate with engineering teams to optimize database structure and improve data quality.
• Document queries, data structures, and one-off scripts for transparency and repeatability.
• Design, develop, and maintain data pipelines and ETL/ELT processes in Azure Cloud environments (Data Factory / Logic Apps / Synapse / Databricks)

Requirements:

• 5+ years of experience in data engineering, analytics, or database administration roles.
• Strong proficiency in SQL (including CTEs, window functions, subqueries).
• Basic proficiency in Python for maintaining and updating existing ETL processes.
• Deep understanding of relational database systems.
• Experience writing safe, efficient data modification scripts for use in production environments.
• Strong communication skills – able to explain technical data issues to non-technical stakeholders.
• Excellent problem-solving and analytical skills.
• Strong attention to detail and ability to work in a fast-paced environment.

Nice to haves:

• Experience working with Azure cloud platforms such as Data Factory, Logic Apps, Synapse etc.
• Experience working with Azure App Insights to identify and resolve application errors resulting from data quality issues.
• Basic proficiency with .NET to enhance investigation into errors within the applications.