Live opening · Posted 5 days ago

Senior Software Engineer

EXL · Pune District, Maharashtra, India (Hybrid)
Linkedin Hybrid
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At a glance

The key details from the original listing.

Posted 5 days ago
CompanyEXL
LocationPune District, Maharashtra, India (Hybrid)
Work modeHybrid
SourceLinkedin
Listed5 days ago

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About the role

Description supplied by the original job listing.

Role: Neo4J Graph Data Engineer – (User Workload Migration)
Location: All-Location
Experience: 7+ Years
Role Overview
We are seeking a Data Engineer to oversee the planning, execution, and validation of our enterprise data migration strategies. In this role, you will be responsible for moving critical data from legacy environments to modern, scalable cloud-based target architectures. You will take ownership of migrating specialized workloads that rely heavily on graph data structures, custom application interfaces, and financial modeling systems.
Key Responsibilities:
Graph Workload Migration: Take charge of migrating complex graph database workloads, translating and optimizing Cypher queries for native cloud graph environments.
Java API Integration: Refactor, deploy, and maintain robust Java APIs to ensure application layers connect seamlessly with the new AWS data ecosystem.
Build the AWS Data Core: Architect and build high-performance, parallel data streams utilizing native cloud services such as AWS Glue, Amazon S3, Lambda, and Athena.
Ensure Data Integrity: Develop automated validation scripts to audit rows, schemas, and relational integrity so that complex user workloads land in AWS with zero data loss.
Optimize & Troubleshoot: Fine-tune data extraction to prevent on-prem bottlenecks, manage API throttling on AWS,
Handson experience on writing scripts python, PySpark
Required Skills & Qualifications
Graph Technologies: Strong practical experience working with graph databases and writing efficient, production-grade Cypher queries.
Java Development: Solid background in Java with experience building, debugging, or migrating enterprise APIs and data connectors.
Enterprise Integrations: Proven experience working with or integrating SAS / SASFM environments into broader data pipelines.
AWS Data Stack: Deep, hands-on experience using core AWS data services—specifically AWS Glue (ETL), Amazon S3, and Amazon Athena. .
Experience & Education
Experience: 7+ years of data engineering experience, with at least 2 years dedicated to migrating legacy workloads to AWS.
Certification (Preferred): AWS Certified Data Engineer – Associate/Professional or AWS Certified Solutions Architect.

Work arrangement
Hybrid

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