What are the responsibilities and job description for the Data Engineer (Java & AWS) - W2 Role position at PROCAL TECHNOLOGIES?
Job Title: Data Engineer (Java & AWS) - W2 Role
Location: Irving, TX (Onsite)
US Citizen/H4EAD/Green Card
Duration: Long-Term Contract
Job Summary
We are seeking an experienced Data Engineer with strong expertise in Java, AWS Cloud, and Big Data technologies to design, develop, and maintain scalable data pipelines and cloud-based data platforms. The ideal candidate should have hands-on experience in distributed data processing, cloud-native applications, ETL development, and modern data engineering practices.
Required Skills
- 8 years of IT experience with 5 years in Data Engineering.
- Strong programming experience in Java (Java 8/11/17).
- Hands-on experience with AWS Cloud Services:
- S3
- EMR
- Glue
- Lambda
- Redshift
- RDS
- DynamoDB
- Kinesis
- Athena
- IAM
- CloudWatch
- Step Functions
- Experience building ETL/ELT pipelines.
- Strong SQL skills and database design.
- Experience with Apache Spark (Java or PySpark).
- Experience with Kafka or other messaging platforms.
- Hands-on experience with Docker and Kubernetes (EKS preferred).
- CI/CD experience using Jenkins, GitHub Actions, or GitLab CI.
- Version control using Git.
- Linux/Unix scripting.
- Experience with REST APIs and Microservices.
- Agile/Scrum methodology.
Preferred Skills
- Python for automation and data processing.
- Terraform or CloudFormation.
- Snowflake or Databricks.
- Airflow or AWS Managed Workflows.
- Data Lake and Lakehouse architecture.
- Experience with Delta Lake or Apache Iceberg.
- Monitoring using Splunk, CloudWatch, or Datadog.
Responsibilities
- Design and develop scalable data pipelines using Java and AWS services.
- Build batch and real-time data ingestion solutions.
- Develop ETL processes for structured and semi-structured data.
- Optimize data processing jobs for performance and scalability.
- Implement data quality, validation, and governance standards.
- Develop cloud-native microservices supporting data platforms.
- Integrate multiple enterprise systems using APIs and event-driven architecture.
- Work with Data Scientists, Analysts, and Business teams to deliver data solutions.
- Implement monitoring, logging, and alerting for data pipelines.
- Troubleshoot production issues and perform root cause analysis.
- Participate in code reviews and follow best coding practices.
- Support CI/CD automation and infrastructure deployment.