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W2 - Principal Data Engineer || Johnston, RI || Hybrid

Job

Cliff Services Inc

Johnston, RI (In Person)

Full-Time

Posted 1 week ago (Updated 3 days ago) • Actively hiring

Expires 7/24/2026

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Job Description

Job Description Principal Data Engineer Location:

Johnston, RI Role Overview Principal-level Java engineer to design and build enterprise-grade, real-time and batch data processing systems using Java, Spark, Kafka, and Microservices architecture. Strong focus on event-driven pipelines, API development (build + consume), and high-volume streaming platforms. Key Responsibilities Architect, design, and implement enterprise-grade Java-based data platforms and distributed processing systems Build and maintain production-ready Spark applications (Java) for batch and real-time processing Design and evolve Kafka-based event streaming and ingestion pipelines Develop and consume REST APIs within microservices architecture Lead architecture ensuring scalability, reliability, and regulatory compliance Apply strong object-oriented design and engineering practices Mentor engineers on performance tuning and production readiness Design and implement MDM solutions (match, merge, survivorship logic) Ensure data quality, observability, and system stability Support production deployments and operational handoffs Required Skills & Experience 10 12+ years experience in Java/backend or data engineering Hands-on experience building real-time data pipelines ( Kafka, Spark Streaming/Flink) Solid knowledge of relational databases (Redshift, PostgreSQL, Snowflake) and NoSQL databases (MongoDB or similar) Strong Kafka and event-driven architecture experience Strong Microservices experience (Spring Boot, REST APIs) Experience in API development and API consumption Hands-on Spark experience (batch and streaming) Strong SQL and data modeling skills AWS experience (S3, Glue, EMR, Redshift) Experience in regulated/data governance environments CI/CD, Git, Docker/Kubernetes familiarity Preferred Scala or Python experience Talend/DataStage exposure Data lake experience (Iceberg/Parquet) Frontend/API integration exposure Experience supporting large-scale production systems Mandatory Screening Criteria Candidates must have hands-on experience building real-time/event-driven data pipelines using Kafka and Spark/Flink, along with strong microservices and API development experience.