Senior Software Engineer (Data, API & Platform Integration)

Senior Data Engineer (API & Platform Integration)

Key Responsibilities

Platform & Data Engineering

• Design build and maintaincloudnative data pipelines and platforms supporting PLS and IAR use cases (e.g. learner activity assessments recommendations analytics).
• Own endtoend data workflows across ingestion transformation storage and serving layers.
• Develop scalable batch and streaming pipelines that meet performance reliability and dataquality expectations.
• Contribute to data modeling standards that support downstream analytics ML and reporting needs.

Reliability Quality & Security

• Ensuredata quality observability and pipeline reliability through monitoring automated validation and alerting.
• Apply Pearsons data security privacy and retention standards in all platform designs.
• Support production incident analysis rootcause identification and longterm remediation.

Collaboration & Leadership

• Collaborate with product managers analytics engineers data scientists and platform teams to align data solutions to business goals.
• Act as atechnical mentor for junior engineers setting best practices for data engineering and platform development.
• Provide technical input into architectural decisions roadmap planning and platform modernization initiatives.

Continuous Improvement

• Drive continuous improvement in tooling frameworks and engineering practices within the PLS / IAR data platform.
• Evaluate emerging technologies and patterns to evolve Pearsons data ecosystem responsibly.

Required Skills & Proficiencies

Pearson Power Skills (Core)

• Collaboration and crossfunctional communication
• Accountability and ownership of outcomes
• Attention to detail and quality
• Ethical responsibility and data stewardship
• Adaptability in a changing technology landscape

RoleBased Technical Skills

• Cloud Computing: Designing and operating data platforms in cloud environments (e.g. AWSbased data services).
• Data Engineering: Building ETL/ELT pipelines orchestration workflows and data models at scale.
• Data Security: Implementing secure data access encryption and governance controls.
• Software Engineering: Writing maintainable testable code using modern engineering practices.
• DevOps / DataOps: CI/CD infrastructureascode and automated deployment of data pipelines.
• Observability: Monitoring logging and alerting for data systems and pipelines

RoleBased Technical Skills Future (Desirable)

• AIenabled and MLadjacent data platform patterns
• Automated data quality and intelligent observability
• Eventdriven and streaming architectures
• Advanced data governance and lineage automation

SeniorLevel Expectations

• Operates independently on complex ambiguous data problems.
• Influences platform and architectural decisions beyond immediate team scope.
• Provides technical leadership and guidance without direct people management.
• Balances longterm platform evolution with shortterm delivery needs.

Working Knowledge (Required)

• Fullstack development concepts including integration withWeb APIs
• Programming languages:Java Python
• AWS cloud services used for data platforms
• Datastores:DynamoDB Aurora DB MongoDB RDBMS
• CI/CD and operational practices supporting data platforms

Candidates local to Hoboken NJ are highly preferred.

Applications will be accepted through May 21. This window may be extended depending on business needs.