Vrinda International
Python Developer – API Data Ingestion
Pune / Hyderabad, INNa miejscuStałaPełny etat
Opublikowano 5 wrz 2026
To stanowisko jest opublikowane w języku EN
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
Przegląd stanowiska
Typ stanowiska
Pełny etat
Wymagane umiejętności
Python developmentAPI protocols (REST, GraphQL, SOAP)API authentication & secrets management (OAuth2, JWT, API Keys, mTLS)Robust API ingestion patterns (pagination, rate limiting, retries/backoff, idempotency, checkpointing, incremental loads)Data validation, reconciliation and data quality metricsData transformation & formats (JSON, XML, CSV, Parquet, Avro to tabular)PII handling and data maskingETL/ELT and data engineering fundamentalsSQL and relational/analytical data storesGCP / cloud data platformsAirflow or equivalent orchestration toolsCI/CD, logging, monitoring and alertingContainerization and orchestration basics (Docker, Kubernetes)SLA and data contract definition & stakeholder collaboration
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