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Vrinda International

Python Developer – API Data Ingestion

Posted One Month Ago
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In-Office or Remote
2 Locations
Senior level
In-Office or Remote
2 Locations
Senior level
Develop and maintain Python-based API data ingestion services for GCP. Build secure, scalable, fault-tolerant pipelines with authentication, incremental loading, validation, reconciliation, orchestration, monitoring, and alerting. Manage data quality, PII masking, CI/CD, production troubleshooting, performance optimization, SLAs, data contracts, technical designs, mappings, and operational documentation. Collaborate with stakeholders to define support models and ensure reliable ingestion from internal and external APIs.
The summary above was generated by AI

 HIRING | Python Developer – API Data Ingestion

 Location: Pune / Hyderabad
 Experience: 5–8 Years
 Salary: ₹19–21 LPA

We are looking for an experienced Python Developer to build and manage reliable API-based data ingestion pipelines, with a strong focus on data quality, security, monitoring and production operations.

? Key Skills & Requirements

• Strong Python development – 3+ years
• REST / GraphQL APIs; SOAP knowledge is an advantage
• API authentication: OAuth2, JWT, API Keys, mTLS
• API pagination, rate limiting, retries & backoff
• Idempotency, checkpointing and incremental loads
• Data validation, reconciliation and quality metrics
• JSON/XML transformation to tabular formats
• PII handling and data masking
• ETL/ELT and data engineering fundamentals
• SQL and relational/analytical data stores
• Data formats: JSON, CSV, Parquet, Avro
• GCP / cloud data platforms
• Airflow or equivalent orchestration tools
• CI/CD, logging, monitoring and alerting
• Docker and Kubernetes basics
• Kafka / event streaming – added advantage
? Key Responsibilities
• Design, develop and maintain Python-based API ingestion services
• Ingest data from internal and external APIs into GCP
• Implement secure authentication and secrets management
• Build robust, scalable and fault-tolerant ingestion pipelines
• Implement incremental loads, data validation and reconciliation
• Orchestrate pipelines using Airflow or equivalent tools
• Implement CI/CD and production monitoring
• Troubleshoot errors and optimize pipeline performance
• Define SLAs, data contracts and support models with stakeholders
• Prepare technical designs, data mappings and operational documentation


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