Backend Integration Engineer

Its fun to work in a company where people truly BELIEVE in what they are doing!

Were committed to bringing passion and customer focus to the business.

Experience: 69 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:
o Salesforce
o SAP
o SharePoint
o Enterprise Databases
o Data Warehouses
o Cloud Storage Services
o 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
Responsibilities
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
Bachelors or Masters degree in Computer Science Information Technology Data Engineering or related field.
610 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
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.

If you like wild growth and working with happy enthusiastic over-achievers youll enjoy your career with us!

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