Senior Software Engineer

Senior Data Engineer (API & Platform Integration)

Key Responsibilities

Platform & Data Engineering

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

Reliability, Quality & Security

• Ensure data quality, observability, and pipeline reliability through monitoring, automated validation, and alerting.
• Apply Pearson's data security, privacy, and retention standards in all platform designs.
• Support production incident analysis, root-cause identification, and long-term remediation.

Collaboration & Leadership

• Collaborate with product managers, analytics engineers, data scientists, and platform teams to align data solutions to business goals.
• Act as a technical 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 Pearson's data ecosystem responsibly.

Required Skills & Proficiencies

Pearson Power Skills (Core)

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

Role-Based Technical Skills

• Cloud Computing: Designing and operating data platforms in cloud environments (e.g., AWS-based 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, infrastructure-as-code, and automated deployment of data pipelines.
• Observability: Monitoring, logging, and alerting for data systems and pipelines

Role-Based Technical Skills – Future (Desirable)

• AI-enabled and ML-adjacent data platform patterns
• Automated data quality and intelligent observability
• Event-driven and streaming architectures
• Advanced data governance and lineage automation

Senior-Level 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 long-term platform evolution with short-term delivery needs.

Working Knowledge (Required)

• Full-stack development concepts, including integration with Web 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.

Compensation at Pearson is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific location. As required by the California, Colorado, Hawaii, Illinois, Maryland, Minnesota, New Jersey, New York State, New York City, Vermont, Washington State, and Washington DC laws, the pay range for this position is as follows:

The full-time salary range for this position is between $120,000 - $140,000

This position is eligible to participate in an annual incentive program, and information on benefits offered is here.