Full Time Dataops Engineer Jobs in New Jersey (NOW HIRING)

Senior Data Engineer (API & Platform Integration)

Key Responsibilities

Platform & Data Engineering

• Design, build, and maintain cloudnative 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

• 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, 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 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 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 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.