Principal Data Engineer

Job Description

Job Description

Job Title: Principal Data Engineer

Job Description – Principal Data Engineer

Job Type: Contract W2

Location: Johnston, RI or Charlotte, NC or Boston,MA

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.