Data Engineering- Azure Databricks- Manager

Overview

Lead Azure Databricks data engineering workstreams and guide teams in cloud-based data modernization and pipeline delivery within PwC's Cloud Engineering, Data & Analytics practice.

What you'll do

• Lead Azure Databricks data engineering workstreams across client delivery and internal modernization initiatives
• Manage project plans, timelines, and deliverables while coordinating resources across multiple data transformation efforts
• Develop scalable data pipelines, integration patterns, and data warehouse solutions for cloud-based analytics environments
• Review data architecture, modeling approaches, and performance tuning methods to improve reliability and query speed
• Apply Azure Data Factory, Apache Airflow, and Databricks Unified Data Analytics Platform capabilities to build and automate data movement processes
• Guide teams in data quality, validation, and troubleshooting activities across complex data platforms
• Coach junior team members through feedback, technical review, and day-to-day problem solving
• Identify opportunities to simplify data infrastructure, strengthen security controls, and support data modernization goals

What you'll need

• At least a Bachelor's degree
• At least 4 years of experience
• Oral and written proficiency in English

Nice to have

• Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
• Demonstrating Azure Databricks data engineering delivery across client engagements
• Utilizing Databricks, Azure Data Factory, and Apache Airflow for pipelines
• Leading teams through data architecture, modeling, and transformation decisions
• Coaching junior staff while managing quality, timelines, and deliverables
• Applying analytical thinking to data quality, validation, and performance tuning