Data Engineer - Senior Manager

PwC•Cincinnati, OH

1d•$124,000 - $280,000•Onsite

About The Position

As a Data Engineer - Senior Manager within PwC's Technology Consulting practice, you will be instrumental in transforming raw data into actionable insights to drive informed decision-making and business growth. Your primary focus will be on designing and building robust data infrastructure and systems for efficient data processing and analysis. This includes developing and implementing data pipelines, data integration, and data transformation solutions. As a Senior Manager, you will leverage your expertise and network to deliver high-quality results, while also motivating and coaching teams to tackle complex problems. You will exercise sound judgment, knowing when to act and when to escalate issues, and will be dedicated to developing and sustaining diverse and inclusive teams. Your commitment to excellence is key to the success of our firm. In this role, you will craft and deliver clear, impactful messages that present a holistic story, apply systems thinking to identify root causes of problems, and validate outcomes with clients. You will guide teams through complex situations with composure, initiate open and honest coaching conversations at all levels, and make difficult decisions to resolve issues that impede team effectiveness.

Requirements

At least a Bachelor's degree
At least 6 years of experience

Nice To Haves

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 proficiency in data engineering platforms like Databricks and Snowflake
Utilizing advanced skills in data architecture development and optimization
Leading teams in implementing data integration and transformation strategies
Applying systems thinking to solve complex data challenges
Excelling in managing data pipelines and confirming data quality
Leveraging cloud platforms such as AWS and Azure for scalable data solutions

Responsibilities

Leading the design and development of data infrastructure and systems to facilitate efficient data processing and analysis
Developing and implementing data pipelines, integration, and transformation solutions to support client needs
Utilizing Amazon Web Services (AWS) and Azure Data Factory to enhance data engineering capabilities
Applying advanced data modeling techniques, including dimensional modeling and Directed Acyclic Graphs (DAGs), to optimize data architecture
Overseeing database management, optimization, and security best practices to maintain data integrity
Collaborating with cross-functional teams to drive data strategy and deliver actionable insights
Promoting the use of innovative technologies such as Apache Hadoop and Databricks Unified Data Analytics Platform
Validating data quality and implementing data anonymization techniques to protect sensitive information
Directing teams through complex data engineering projects, demonstrating composure in challenging situations
Coaching and mentoring team members to develop high-performing, diverse, and inclusive teams