Principal-level Java engineer

P2PSoftTek Inc

Charlotte, NC, United States

about 2 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

dice.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Amazon Web Services Amazon S3 Continuous Integration Information Engineering Data Governance Relational Databases IBM InfoSphere DataStage Distributed Computing Environment Python (Programming Language) PostgreSQL

+31 more

MongoDB NoSQL Object-Oriented Software Development Performance Tuning Standard Sql Software Deployment Data Streaming Talend Parquet Data Processing Real Time Systems Data Ingestion Snowflake Apache Spark Spring-boot Backend Git Event Driven Architecture Data Lakes Kubernetes Apache Flink Apache Kafka Spark Streaming Data Management Front End Software Development Api Design Restful APIs Data Pipelines Docker Amazon Redshift Microservices

Job description

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., * 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

Requirements

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, 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.