Backend Integration Engineer

Fractal Analytics Ltd.; Bengaluru; On-site; INR 1,400,000 - 2,100,000; Full time

Job summary

Fractal Analytics Ltd. is seeking an experienced Backend / Integration Engineer to design, develop, integrate, and support enterprise-scale data platforms.

The role focuses on Python development, ETL/ELT frameworks, PySpark, API engineering, and cloud-based connectivity across CRM, ERP, SharePoint, databases, data warehouses, and SaaS platforms. You will build scalable backend services, data pipelines, and integrations, enabling real-time data movement, governance, and secure enterprise

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.
• Strong expertise in Python development.
• Hands‑on experience building enterprise integrations and APIs.
• Strong understanding of distributed systems and cloud architectures.
• Experience working in Agile development environments.

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 Salesforce, SAP, SharePoint, and databases.
• 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.
• 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.
• 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.
• Develop distributed data processing solutions using PySpark.
• Build large-scale data transformation pipelines.
• 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.

Skills

Python

PySpark

APIs

ETL/ELT

Cloud

Integration

SQL

Docker

Kubernetes

Git

Education

Bachelor's or Master's in CS/IT

Tools

Docker

Kubernetes

Git

CI/CD

Job description

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. Experience: 6–9 Years Location Hybrid / Remote

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.

Key Responsibilities

Backend Application Development

• 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.

Enterprise Integration Engineering

• Design and implement integrations across enterprise applications and platforms.
• Develop and maintain integrations with:
  • Salesforce
  • SAP
  • SharePoint
  • Enterprise Databases
  • Data Warehouses
  • Cloud Storage Services
  • 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.

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.

ETL / Data Pipeline Development

• 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.

Big Data & Data Engineering

• Develop distributed data processing solutions using PySpark.
• Build large-scale data transformation pipelines.
• 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.

Database Engineering & Administration

• Design and maintain relational and analytical data models.
• Develop database schemas, views, stored procedures, and performance optimization strategies.
• Manage enterprise databases including:
  • Databases
  • PostgreSQL
  • MySQL
  • Cloud Databases
  • Data Warehouses
• Query optimization
• Database performance tuning
• Data integrity management
• Backup and recovery support
• Capacity planning

Cloud Data Engineering

• 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:
  • AWS Glue
  • S3
  • Lambda
  • ECS/EKS
  • API Gateway
  • RDS

Data Governance & Security

• Implement enterprise data governance standards.
• 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.

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.

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.
• Strong expertise in Python development.
• Hands‑on experience building enterprise integrations and APIs.
• Strong understanding of distributed systems and cloud architectures.
• Experience working in Agile development environments.

Required Technical Skills

• Programming & Backend Development: Python, SQL, Object‑Oriented Programming, Microservices Architecture, REST APIs, Event‑Driven Architecture
• Data Engineering: ETL / ELT Development, PySpark, Data Transformation, Data Quality Management, Data Validation Frameworks, Batch and Streaming Pipelines
• Enterprise Integration: Salesforce Integration, SAP Integration, SharePoint Integration, API Integration, SaaS Platform Integration, Message‑Based Architectures
• Databases: PostgreSQL, MySQL, etc, Relational Database Design, Query Optimization, Database Performance Tuning
• Cloud Technologies: AWS, AWS Glue, S3, Lambda, Cloud Storage
• DevOps: Git, CI/CD Pipelines, Docker, Kubernetes, Monitoring & Observability
• Governance & Security: Data Governance, Data Lineage, Metadata Management, Data Privacy, Security Best Practices, Compliance Frameworks

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.

Success Profile

• 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.

If you like wild growth and working with happy, enthusiastic over‑achievers, you'll enjoy your career with us!

At Fractal, towards our goal of “powering every human decision in the enterprise”, our partnerships and alliances help in creating and delivering a compelling suite of solutions to unlock value. We partner with companies from around the globe, leaders in their respective fields. With Fractal’s expertise in artificial intelligence, design, engineering, and digital transformation, combined with the data, technology, and software platforms from our partners, we create cutting‑edge solutions to problems in the business world. We understand how critical and timely decision triggers, and information, empower our clients to create, unlock, deliver, and realize value. Together with our partners, our goal is to serve each client in their end‑to‑end data‑to‑decision journey.