Data Validation Risk - Senior Associate

PwC•Washington, DC

2d•$77,000 - $202,000•Remote

About The Position

As a Data Validation Risk Senior Associate, you will support client engagements in data and analytics engineering, focusing on data engineering work that helps turn raw information into insights through data pipelines, data integration, and data transformation solutions. As a Senior Associate, you will analyze complex problems, build meaningful client connections, mentor junior team members, and use critical thinking to navigate ambiguity while contributing to workstreams that support the broader objectives of your role within our Risk & Regulatory practice. In this role at PwC, you will help design and develop data solutions, interpret data to inform recommendations, and uphold professional and technical standards while growing your personal brand and technical skills.

Requirements

At least a Bachelor's degree
At least 3 years of experience

Nice To Haves

Preference for at least one of the following fields of study: Analytics/Data Science, Business Administration/Management, Computer Science/Information Systems, Economics, Engineering, Finance, Mathematics/Statistics, Operations/Supply Chain
Demonstrating data validation, data quality, and data integration project experience
Interpreting data findings into recommendations for client-facing delivery teams
Using critical thinking to break down complex data issues
Applying Agile methods and adapting to changing priorities
Building client relationships while guiding junior team members
Upholding technical standards and independence requirements

Responsibilities

Developing data validation approaches for client engagements and translating business requirements into technical controls
Analyzing complex data sets to identify anomalies, breakpoints, and transformation issues across data pipelines
Applying data engineering methods to support data integration, data quality checks, and data transformation activities
Interpreting validation findings and documenting issues, assumptions, and recommended corrective actions
Collaborating with client teams to understand data sources, target structures, and reporting requirements
Reviewing assigned workstreams and supporting junior team members through technical guidance and feedback
Using analytical tools and SQL-based techniques to test data movement, reconcile outputs, and trace data lineage
Monitoring project progress, adapting to changing priorities, and maintaining focus on deliverables and timelines