Data Engineer - Java, AWS, Python

We are looking for a Java Data Engineer to design, build, and maintain scalable data pipelines and data processing solutions. The role involves working closely with data architects, analysts, and engineers to develop high-performance data workflows, ensure data quality, and support analytics initiatives.

Work location : Amsterdam, Netherlands

Role type- Hybrid (2days WFO)

Notice Period- 0-30days

Exp Range- 8+yrs Roles & Responsibilities Key Responsibilities:

Develop and maintain data pipelines using Java.

Design and implement ETL/data transformation processes.

Work with large-scale datasets using Big Data technologies.

Develop and optimize SQL/NoSQL databases and data models.

Ensure data quality, integrity, and performance.

Collaborate with cross-functional teams on data solutions.

Monitor and troubleshoot data processing systems.

Mandatory Skills Java & Spring Boot: Strong hands-on experience in Java development with Spring Boot for building scalable, high-performance microservices and backend applications.

Experience in System Designing & Microservices

Python: Proficiency in Python for data processing, automation, ETL development, and scripting.

AWS Data Services

AWS Lambda for serverless data processing.

AWS Glue for ETL and data integration workflows.

Amazon S3 for data storage and data lake implementations.

Amazon DynamoDB for NoSQL database solutions.

AWS Step Functions for workflow orchestration and automation.

AWS DMS (Database Migration Service) for database migration and replication.

Amazon Athena for querying and analyzing large datasets directly from S3.

Experience in designing and developing data pipelines, ETL/ELT processes, and cloud-native data solutions.

Understanding of data modeling, data integration, and data transformation best practices.

Good-to-Have Skills Terraform for Infrastructure as Code (IaC) and cloud resource provisioning.

Experience with CI/CD pipelines using tools such as Jenkins, GitHub Actions, GitLab CI/CD, or Azure DevOps.

Knowledge of DevOps practices for automated deployment and infrastructure management. Additional/Preferred Skills Snowflake for cloud data warehousing and analytics.

dbt (Data Build Tool) for data transformation and modeling.

Dagster for workflow orchestration, data pipeline management, and observability.

Experience with modern data platforms, data lake architectures, and analytics solutions.

Familiarity with data governance, monitoring, and optimization of large-scale data environments.

Ideal Candidate

Profile A strong Data Engineer with expertise in Java, Python, and AWS data services, capable of building scalable data platforms, developing robust ETL pipelines, and implementing cloud-native data solutions.

Experience with Snowflake, dbt, and Dagster would be a strong advantage.