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Java Data Engineer Jobs in Fernandina Beach, FL (NOW HIRING)

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How much do java data engineer jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for java data engineer in Fernandina Beach, FL is $55.95, according to ZipRecruiter salary data. Most workers in this role earn between $46.06 and $63.22 per hour, depending on experience, location, and employer.

What is a Java data engineer?

A Java Data Engineer is a technology professional who designs, develops, and maintains data processing systems using Java programming language. They work with large datasets, build data pipelines, and ensure the efficient movement, transformation, and storage of data. Java Data Engineers often collaborate with data scientists, analysts, and other engineers to support data-driven decision-making in organizations. Their expertise typically includes Java, SQL, big data technologies like Hadoop or Spark, and cloud platforms. They play a crucial role in enabling reliable and scalable data infrastructure for businesses.

What are the key skills and qualifications needed to thrive as a Java data engineer?

To thrive as a Java Data Engineer, you need strong programming skills in Java, a solid understanding of data structures, SQL, and experience with big data frameworks, often supported by a degree in computer science or a related field. Familiarity with data processing tools like Apache Spark, Hadoop, Kafka, and experience with cloud data platforms (e.g., AWS, GCP) or relevant certifications are typically required. Analytical thinking, problem-solving ability, and effective communication are crucial soft skills for collaborating with teams and interpreting data requirements. These capabilities are essential for building reliable, scalable data solutions that support business intelligence and analytics needs.

What are the most common challenges faced by Java data engineers when working with large-scale data pipelines?

Java Data Engineers often encounter challenges with optimizing the performance and scalability of data pipelines, especially as data volumes grow. They must ensure data integrity and consistency while managing distributed systems and integrating with various data sources. Debugging issues in real-time data processing and maintaining efficient, fault-tolerant code are also key hurdles. Collaborating closely with data scientists, database administrators, and DevOps teams is essential to overcome these challenges and deliver reliable data solutions.

What is the difference between Java Data Engineer vs Python Data Engineer?

AspectJava Data EngineerPython Data Engineer
Required CredentialsBachelor's in Computer Science, Java certificationsBachelor's in Computer Science, Python certifications
Work EnvironmentBig data platforms, Java-based toolsData analysis, scripting, Python-based tools
Employer & Industry UsageFinancial services, enterprise systemsTech startups, data science projects
Common Search & ComparisonYesYes

Java Data Engineers and Python Data Engineers often share similar roles in data processing and engineering. The main difference lies in the programming languages used: Java is common in large-scale enterprise environments, while Python is favored for data analysis and scripting. Both roles require strong programming skills, but their toolsets and typical applications differ based on industry needs.

What cities near Fernandina Beach, FL are hiring for Java Data Engineer jobs?

Cities near Fernandina Beach, FL with the most Java Data Engineer job openings:

Java Data Engineer jobs near you
Infographic showing various Java Data Engineer job openings in Fernandina Beach, FL as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $116,386 per year, or $56 per hour.

Information Technology_USA - USA_Engineer

Real Soft, Inc.

Jacksonville, FL • On-site

$106K - $127K/yr

Contractor

Re-posted 17 days ago

Job description

**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

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