Data Engineer - API & Platform Integration

Hiring for: One of India’s leading non-banking financial companies (NBFCs), focused on driving financial inclusion across rural and semi-urban markets.

Role: Data Engineer - API & Platform Integration

Positions: 1

Experience: 2 to 5 years

Location(s): Kurla, Mumbai

Type: On-site / Permanent

Salary: Up to INR 19 LPA (Including 5% to 10% variable pay)

JOB DESCRIPTION

Department: Data & Analytics

Reports to: Team Lead – Data and Analytics

1. Job Purpose Statement

To strategically lead and support the API and Data Engineering function, enabling secure, scalable, and high-performance integration and data processing capabilities across the organization. This role is responsible for hands-on design, development, and deployment of APIs and data pipelines using modern technologies such as FastAPI, REST APIs, Databricks, and SQL, while leveraging containerization and cloud-native platforms including Docker, Azure Container Apps (ACA), and AKS.

The role ensures seamless data movement and transformation through tools like Azure Data Factory (ADF) or equivalent, aligns API-led integration and data engineering initiatives with business and digital priorities, and provides expert guidance on microservices architecture, data platforms, and best practices within a scalable Lakehouse ecosystem.

2. Duties & Responsibilities 

• Design, develop, and maintain API-led integration solutions and data engineering pipelines to support business applications

• Build and enhance scalable REST APIs using frameworks such as FastAPI, ensuring high performance and reliability

• Develop and optimize data processing workflows using Databricks (PySpark, SQL) for efficient data transformation and analytics

• Collaborate with business and technical teams to understand requirements and translate them into robust API and data solutions

• Implement containerized applications using Docker and deploy/manage services on cloud platforms such as Azure Container Apps (ACA) and AKS

• Develop and manage data integration workflows using Azure Data Factory (ADF) or equivalent to enable seamless data movement across systems

• Ensure adherence to best practices in API design, microservices architecture, security, and performance optimization

• Troubleshoot, debug, and resolve issues related to APIs, data pipelines, and cloud deployments

• Stay updated with emerging technologies and continuously improve technical skills in API engineering, cloud-native development, and data platforms

 3. Key Challenges

• Ensuring high performance, scalability, and reliability of REST APIs under varying workload conditions

• Managing secure API integrations and data exchange across multiple systems with proper authentication and governance

• Deploying, monitoring, and optimizing containerized applications on Docker, ACA, and AKS environments

• Handling large-scale data processing and optimization in Databricks (PySpark, SQL) while maintaining efficiency

• Troubleshooting and maintaining stability across APIs, data pipelines, and cloud-native infrastructure

4. Job Requirements

  Professional Qualification

·      Bachelor’s or master’s degree in computer science, Information Technology, Engineering, or related field with 4–8 years of experience in API development and Data Engineering

Knowledge

·       Knowledge of Gen AI tools

·       Strong understanding of REST API design principles and microservices architecture

·       Knowledge of FastAPI (or similar frameworks) and API development best practices

·       Understanding of Databricks (PySpark, SQL) and data engineering concepts

·       Knowledge of data pipelines, ETL processes, and data flow design

·       Familiarity with Docker, containerization, and cloud platforms (ACA, AKS)

·       Understanding of Azure Data Factory (ADF) or equivalent for data orchestration

·       Knowledge of SQL for querying, optimization, and database design

·       Awareness of API security (OAuth, JWT, authentication/authorization mechanisms)

·       Banking/NBFC domain knowledge will be an added advantage

·       Knowledge of Gen AI tools and their application in development

Skills

·       Develop scalable and high-performance REST APIs using FastAPI

·       Strong hands-on experience with Databricks (PySpark, SQL) for data processing

·       Experience in building and managing data pipelines and integrations

·       Proficiency in SQL for data querying, transformation, and optimization

·       Hands-on experience with Docker and deployment on ACA/AKS environments

·       Ability to develop and manage workflows using Azure Data Factory (ADF) or equivalent

·       Good understanding of database design and data architecture

·       Strong debugging, troubleshooting, and performance tuning skills

·       Python programming for API development and data engineering use cases