Java Data Engineer

We are seeking a highly motivated Java Data Engineer to design, develop, and maintain scalable data pipelines and distributed data processing systems. The ideal candidate will have expertise in Java, big data technologies, cloud platforms, and ETL development. You will work closely with data scientists, software engineers, and business stakeholders to build robust data solutions that enable analytics and business intelligence., * Design, develop, and maintain scalable data pipelines using Java.

• Build and optimize ETL/ELT workflows for processing large datasets.
• Develop high-performance data ingestion, transformation, and integration solutions.
• Design and maintain distributed data processing applications using Spark or Hadoop.
• Develop RESTful APIs for data services and integrations.
• Optimize SQL queries and database performance.
• Implement data quality, validation, and monitoring processes.
• Collaborate with cross-functional teams to understand business data requirements.
• Troubleshoot production data issues and optimize pipeline performance.
• Ensure data security, governance, and compliance standards are followed.
• Participate in Agile development, code reviews, and architecture discussions.
• Maintain technical documentation and best practices.

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field.
• 3 years of experience in Java development.
• Experience with data engineering or ETL development.
• Strong proficiency in Java (Java 8/11/17).
• Experience with Spring Boot.
• Strong SQL and database design skills.
• Experience working with relational and NoSQL databases.
• Experience building REST APIs.
• Familiarity with Linux/Unix environments.
• Experience with Git and version control.
• Knowledge of Agile/Scrum methodologies.

Preferred Qualifications

• Experience with Apache Spark, Hadoop, or Apache Flink.
• Knowledge of Kafka or other messaging platforms.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Experience with data lakes and data warehouses.
• Familiarity with containerization using Docker and Kubernetes.
• Experience with Airflow or workflow orchestration tools.
• Knowledge of data modeling and dimensional modeling.
• Experience with CI/CD pipelines.

Technical Skills Programming Languages

• Java 8/11/17
• SQL
• Python (Preferred)
• Scala (Nice to Have)

Frameworks

• Spring Boot
• Spring Batch
• Spring Data
• Hibernate

Big Data Technologies

• Apache Spark
• Hadoop
• Hive
• Apache Flink
• Apache Kafka
• Apache NiFi

ETL & Workflow

• Apache Airflow
• Talend
• Informatica
• Spring Batch

Databases

• PostgreSQL
• MySQL
• Oracle
• SQL Server
• MongoDB
• Cassandra
• Redis

Cloud Platforms

• AWS
• S3
• EMR
• Glue
• Redshift
• Lambda
• Microsoft Azure
• Azure Data Factory
• Azure Synapse
• Azure Blob Storage
• Google Cloud Platform
• BigQuery
• Dataflow
• Cloud Storage

Data Warehousing

• Snowflake
• Amazon Redshift
• Google BigQuery
• Azure Synapse Analytics

DevOps & CI/CD

• Docker
• Kubernetes
• Jenkins
• GitHub Actions
• Azure DevOps

Version Control

• Git
• GitHub
• GitLab
• Bitbucket

Monitoring & Logging

• Splunk
• ELK Stack (Elasticsearch, Logstash, Kibana)
• Grafana
• Prometheus

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and collaboration skills.
• Ability to work independently and in a team environment.
• Strong attention to detail.
• Good organizational and time management skills.
• Ability to manage multiple projects and deadlines.

Preferred Experience

• Experience building enterprise-scale data platforms.
• Experience processing structured and unstructured data.
• Knowledge of streaming data architectures.
• Experience optimizing large-scale data pipelines.
• Familiarity with data governance and security practices.
• Experience working in Agile development teams.

Nice to Have

• Apache Beam
• Delta Lake
• Databricks
• Iceberg
• Hudi
• Terraform
• dbt
• OAuth/JWT Authentication
• Microservices Architecture
• Event-Driven Architecture
• Machine Learning data pipelines
• Real-time analytics platforms