Back End Developer

Fractal; Bengaluru; On-site; INR 1,500,000 - 2,200,000; Full time

Job summary

Fractal in Bengaluru invites an experienced Backend / Integration Engineer to design, develop, and support enterprise-scale data and application platforms. You will build scalable backend services, data pipelines, and integrations across CRM, ERP, and cloud services using Python and API-first approaches.

The role emphasizes secure, reliable architectures, event- and API-driven patterns, and collaboration with data scientists, analytics teams, and AI engineers to enable governed, near real-time

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.
• 6–10 years of software engineering and integration experience.
• Hands-on experience building enterprise integrations and APIs.
• Strong understanding of distributed systems and cloud architectures.

Responsibilities

• Design, develop, and maintain scalable backend applications and services using Python.
• Build high-performance APIs, microservices, and distributed processing frameworks.
• Develop reusable backend components, integration frameworks, and utility services.
• Implement secure, scalable, and maintainable application architectures.
• Troubleshoot and optimize application performance and reliability.
• Design and implement integrations across enterprise applications and platforms.
• Develop and maintain integrations with SAP, SharePoint, Data Warehouses, External APIs and SaaS platforms.
• Build event-driven and API-driven integration architectures.
• Support batch, real-time, and near real-time integration patterns.
• Monitor integration health and resolve operational issues.

Skills

Python development

ETL/ELT frameworks

PySpark

API engineering

Cloud-based data integration

Enterprise connectivity

Distributed systems

Education

Bachelor's or Master's in CS/IT or related

Tools

SAP

SharePoint

Data Warehouses

External APIs & SaaS Platforms

Job description

Note - immediate to 30 days' notice period required

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Role Summary

We are seeking an experienced Backend / Integration Engineer to design, develop, integrate, and support enterprise-scale data and application platforms. The ideal candidate will have strong expertise in Python development, ETL/ELT frameworks, PySpark, API engineering, cloud-based data integration, and enterprise application connectivity.

This role will be responsible for building scalable backend services, data pipelines, and integrations across business systems such as CRM, ERP, collaboration platforms, databases, cloud services, and AI-driven applications. The engineer will play a key role in enabling seamless data movement, data quality, governance, and near real-time business process integration.

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Key Responsibilities

• Design, develop, and maintain scalable backend applications and services using Python.
• Build high-performance APIs, microservices, and distributed processing frameworks.
• Develop reusable backend components, integration frameworks, and utility services.
• Implement secure, scalable, and maintainable application architectures.
• Troubleshoot and optimize application performance and reliability.
• Design and implement integrations across enterprise applications and platforms.
• Develop and maintain integrations with:
• SAP
• SharePoint
• Data Warehouses
• External APIs and SaaS Platforms
• Build event-driven and API-driven integration architectures.
• Support batch, real-time, and near real-time integration patterns.
• Monitor integration health and resolve operational issues.

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API Development & Management

• Design and develop RESTful APIs and integration services.
• Create secure authentication and authorization mechanisms.
• Develop API orchestration and service integration layers.
• Build reusable API frameworks and developer-friendly services.
• Support API documentation, versioning, and lifecycle management.

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• Design and build enterprise ETL/ELT pipelines.
• Develop scalable data ingestion, transformation, and enrichment processes.
• Automate data extraction from multiple enterprise systems.
• Build data validation, reconciliation, and auditing mechanisms.
• Optimize data movement, processing efficiency, and reliability.
• Support structured and unstructured data processing workloads.
• Optimize Spark jobs for performance, scalability, and cost efficiency.
• Collaborate with data scientists, AI engineers, and analytics teams.
• Design and maintain relational and analytical data models.
• Develop database schemas, views, stored procedures, and performance optimization strategies.

Databases

• Database performance tuning
• Data integrity management
• Backup and recovery support
• Capacity planning

• Build and operate data platforms on AWS and GCP.
• Develop cloud-native integration and data processing solutions.
• Implement scalable data architectures on cloud environments.
• Manage cloud data pipelines and infrastructure.

AWS Services

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Data Governance & Security

• Ensure compliance with data quality, retention, lineage, and security requirements.
• Support metadata management and data catalog initiatives.
• Ensure proper handling of sensitive and regulated information.
• Work closely with governance and security teams to maintain compliance standards.

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DevOps & Deployment

• Build and maintain CI/CD pipelines for backend services.
• Support automated deployments and release management processes.
• Implement monitoring, logging, and observability frameworks.
• Support production operations and incident management.

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Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.
• 6–10 years of software engineering and integration experience.
• Hands-on experience building enterprise integrations and APIs.
• Strong understanding of distributed systems and cloud architectures.

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Required Technical Skills

• Data Quality Management
• Batch and Streaming Pipelines
• Message-Based Architectures
• Databases
• DevOps
• Governance & Security
• Security Best Practices

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Preferred Qualifications

• Experience supporting AI/ML and GenAI data platforms.
• Experience building Retrieval-Augmented Generation (RAG) data pipelines.
• Exposure to vector databases and enterprise search platforms.
• Experience with workflow orchestration platforms.
• Knowledge of Master Data Management (MDM).
• Familiarity with data catalog and governance tools.

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Success Profile

The successful candidate will:

• Build scalable and reliable backend systems that power enterprise applications and AI platforms.
• Deliver robust integrations across business-critical systems including Salesforce, SAP, SharePoint, and databases.
• Develop high-quality ETL pipelines and data engineering solutions.
• Enable trusted, governed, and secure enterprise data ecosystems.
• Drive cloud-native modernization and automation initiatives.
• Partner effectively with product, AI, analytics, and business teams to deliver measurable business value.