Advanced Specialist, Data Engineering

Pearson•Bloomington, MN

About The Position

Pearson Professional Assessments is seeking a Data Architect to lead the design and evolution of the data ecosystem supporting advanced data forensics, fraud detection, investigative analytics, and threat intelligence. This role will establish the architecture, governance, and technical foundations necessary to deliver scalable analytics, machine learning, and investigative intelligence capabilities across a global assessment environment. The successful candidate will combine strategic architectural vision with hands-on expertise in cloud data platforms, data engineering, and analytics enablement.

Requirements

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related discipline.
5+ years of experience in Data Architecture, Data Engineering, Analytics Architecture, or related fields.
Strong experience with: Azure Data Platform technologies, Databricks SQL, Enterprise Data Modeling, Data Lake and Data Warehouse architectures, ETL/ELT design patterns.
Experience designing and implementing enterprise-scale data solutions.
Strong understanding of governance, data quality, and information management principles.

Nice To Haves

Experience supporting cybersecurity, fraud prevention, investigation, risk, or intelligence functions.
Experience with: Azure Synapse, Azure Data Factory, Microsoft Fabric, Spark, Delta Lake, Power BI.
Familiarity with machine learning infrastructure and deployment architectures.
Experience in highly regulated or security-sensitive environments.
Knowledge of privacy, compliance, and information security frameworks.

Responsibilities

Design and maintain enterprise-scale data architectures supporting forensic analytics and security operations.
Define standards for data modeling, integration, quality, lineage, and governance.
Develop target-state architectures that support both operational reporting and advanced analytical workloads.
Create architectural roadmaps that align with business and security objectives.
Architect and optimize cloud-based analytics platforms utilizing Azure and Databricks technologies.
Design scalable solutions supporting data lakes, warehouses, and analytical processing environments.
Ensure performance, reliability, scalability, and resiliency across the data ecosystem.
Design frameworks for integrating data from: Test delivery systems, Remote proctoring platforms, Identity verification systems, Security technologies, Investigation and case management platforms, Internal and external intelligence sources.
Establish standards for batch, real-time, and streaming data pipelines.
Implement enterprise data governance standards and controls.
Ensure appropriate data security, privacy, retention, and compliance requirements are met.
Establish data quality monitoring and remediation processes.
Support audit, regulatory, and compliance initiatives as required.
Build and maintain architectures that support machine learning, artificial intelligence, and advanced analytics workloads.
Partner with Data Scientists to optimize data access and analytical workflows.
Develop reusable data products and services that accelerate analytical development.
Serve as a trusted advisor on data architecture decisions.
Evaluate emerging technologies and architectural patterns.
Mentor technical teams on data management best practices.
Partner with stakeholders across security, technology, and business organizations.