Information Technology_USA - USA_Engineer
Real Soft, Inc.
Jacksonville, FL, USA
7/22/2026
Engineering
Full time
**Please strictly adhere to the following resume naming convention:
ALL CAPS, NO SPACES BETWEEN UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
Example: PTN_US_9999999_SKIPJOHNSON0413
: -
MSP Owner: Michelle Lee
Location: Seattle, WA
Duration: 6 months
skill id: 10882397
Role Overview
We are seeking a highly skilled Data Streaming Engineer with strong expertise in Apache Flink and Apache Spark to design, develop, and optimize large-scale real-time and batch data processing solutions. The ideal candidate will have hands-on experience building high-performance streaming pipelines, event-driven architectures, and enterprise-grade data platforms.
Required Technical Skills
Apache Flink
• Strong hands-on experience in Apache Flink DataStream API.
• Expertise in Apache Flink Table API & SQL API.
• Experience designing and implementing:
o Stateful stream processing
o Event-time processing
o Windowing operations
o Checkpointing and fault tolerance
o Watermarks and late event handling
• Knowledge of Flink deployment and operations in distributed environments.
Apache Spark
• Strong proficiency in:
o Spark Core
o Spark SQL
o Structured Streaming
• Experience developing high-volume ETL and data transformation pipelines.
• Performance tuning and optimization of Spark jobs.
• Knowledge of Spark execution architecture and resource management.
Responsibilities
• Design, develop, and maintain scalable real-time data processing pipelines.
• Build streaming applications using Apache Flink and Spark Structured Streaming.
• Develop batch and near real-time ETL workflows.
• Process and analyze large-scale datasets with low latency and high throughput.
• Optimize data pipelines for performance, reliability, and scalability.
• Collaborate with Data Engineers, Architects, and Business Stakeholders to deliver data solutions.
• Implement monitoring, logging, and troubleshooting for data processing applications.
• Ensure data quality, governance, and security standards are followed.
Preferred Skills
• Experience with Kafka, Event Hubs, or other messaging/streaming platforms.
• Knowledge of distributed systems and microservices architecture.
• Experience with cloud platforms (Azure, AWS, or GCP).
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Experience with CI/CD pipelines and DevOps practices.
• Proficiency in Java, Scala, or Python.
Key Competencies
• Real-Time Data Processing
• Stream Processing Architecture
• Data Engineering & ETL
• Performance Optimization
• Distributed Computing
• Problem Solving & Analytical Thinking
• Agile Development Methodologies
Primary Skillset: Apache Flink (DataStream API, Table API, SQL API), Apache Spark (Core, SQL, Structured Streaming)
Secondary Skillset: Kafka, Azure/AWS, Python/Java/Scala, Kubernetes, Data Lakes, CI/CD
Skills: Digital : Apache Spark ~ Data Architecture and Modeling
Experience Required: 8-10
ALL CAPS, NO SPACES BETWEEN UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
Example: PTN_US_9999999_SKIPJOHNSON0413
: -
MSP Owner: Michelle Lee
Location: Seattle, WA
Duration: 6 months
skill id: 10882397
Role Overview
We are seeking a highly skilled Data Streaming Engineer with strong expertise in Apache Flink and Apache Spark to design, develop, and optimize large-scale real-time and batch data processing solutions. The ideal candidate will have hands-on experience building high-performance streaming pipelines, event-driven architectures, and enterprise-grade data platforms.
Required Technical Skills
Apache Flink
• Strong hands-on experience in Apache Flink DataStream API.
• Expertise in Apache Flink Table API & SQL API.
• Experience designing and implementing:
o Stateful stream processing
o Event-time processing
o Windowing operations
o Checkpointing and fault tolerance
o Watermarks and late event handling
• Knowledge of Flink deployment and operations in distributed environments.
Apache Spark
• Strong proficiency in:
o Spark Core
o Spark SQL
o Structured Streaming
• Experience developing high-volume ETL and data transformation pipelines.
• Performance tuning and optimization of Spark jobs.
• Knowledge of Spark execution architecture and resource management.
Responsibilities
• Design, develop, and maintain scalable real-time data processing pipelines.
• Build streaming applications using Apache Flink and Spark Structured Streaming.
• Develop batch and near real-time ETL workflows.
• Process and analyze large-scale datasets with low latency and high throughput.
• Optimize data pipelines for performance, reliability, and scalability.
• Collaborate with Data Engineers, Architects, and Business Stakeholders to deliver data solutions.
• Implement monitoring, logging, and troubleshooting for data processing applications.
• Ensure data quality, governance, and security standards are followed.
Preferred Skills
• Experience with Kafka, Event Hubs, or other messaging/streaming platforms.
• Knowledge of distributed systems and microservices architecture.
• Experience with cloud platforms (Azure, AWS, or GCP).
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Experience with CI/CD pipelines and DevOps practices.
• Proficiency in Java, Scala, or Python.
Key Competencies
• Real-Time Data Processing
• Stream Processing Architecture
• Data Engineering & ETL
• Performance Optimization
• Distributed Computing
• Problem Solving & Analytical Thinking
• Agile Development Methodologies
Primary Skillset: Apache Flink (DataStream API, Table API, SQL API), Apache Spark (Core, SQL, Structured Streaming)
Secondary Skillset: Kafka, Azure/AWS, Python/Java/Scala, Kubernetes, Data Lakes, CI/CD
Skills: Digital : Apache Spark ~ Data Architecture and Modeling
Experience Required: 8-10