User Workload Engineer.
This mandate is run by SYMPHONI HR, a Mumbai-based executive search firm, est. 2003. Applications are email-verified and reach the search team running the role — confidentially, always.
About the organisation.
Our client is a leading global computer software organization known for delivering innovative enterprise solutions. They operate at a significant scale, supporting complex data ecosystems for a diverse range of international clients. The company fosters a collaborative, high-performance culture that prioritizes technological advancement and professional growth.
About the role.
We are seeking a skilled Data Engineer to lead the planning, execution, and validation of enterprise-level data migration strategies. You will be responsible for transitioning critical workloads from legacy environments to modern, scalable cloud-based architectures. This role focuses on integrating specialized financial modeling systems and graph data structures into a robust AWS ecosystem.
What you will do.
- Refactor, deploy, and maintain robust Java APIs to ensure seamless connectivity between application layers and the AWS data ecosystem.
- Architect and build high-performance, parallel data streams utilizing native cloud services including AWS Glue, Amazon S3, and Amazon Athena.
- Develop automated validation scripts to audit rows, schemas, and relational integrity to ensure zero data loss during migration.
- Optimize data extraction processes to eliminate on-premise bottlenecks and manage API throttling within AWS.
- Collaborate with cross-functional teams to migrate complex user workloads and custom application interfaces.
- Utilize Python and PySpark to build scalable data processing pipelines.
- Provide technical expertise in troubleshooting migration issues and ensuring system performance post-deployment.
What you bring.
- 7–12 years of professional experience in data engineering, with a strong focus on legacy-to-cloud migrations.
- Expertise in Java development, specifically in building, debugging, and migrating enterprise APIs and data connectors.
- Deep hands-on experience with the AWS data stack, including AWS Glue, Amazon S3, and Amazon Athena.
- Proven experience integrating SAS or SASFM environments into broader data pipelines.
- Proficiency in Python and PySpark for data manipulation and pipeline development.
- Strong understanding of data migration best practices and relational database integrity.
- AWS Certified Data Engineer or AWS Certified Solutions Architect certification is highly preferred.
- Familiarity with Hadoop and Neo4j is considered a significant advantage.
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