Data Engineer

Cliff Services Inc
Johnston, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Johnston, United States of America

Tech stack

Java
API
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Continuous Integration
Information Engineering
Data Governance
Relational Databases
IBM InfoSphere DataStage
Distributed Computing Environment
Python
PostgreSQL
MongoDB
NoSQL
Object-Oriented Software Development
Performance Tuning
Standard Sql
Software Deployment
Data Streaming
Talend
Parquet
Data Processing
Data Ingestion
Snowflake
Spark
Spring-boot
Backend
GIT
Event Driven Architecture
Data Lake
Kubernetes
Apache Flink
Kafka
Spark Streaming
Data Management
Front End Software Development
Api Design
REST
Data Pipelines
Docker
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

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.

Apply for this position