Cloud Developer

Tata Consultancy Services; Pune District; On-site; INR 1,200,000 - 2,200,000; Full time

Job summary

Tata Consultancy Services is seeking a skilled Python developer to design and deploy cloud-native applications across Pune, Hyderabad, Chennai, and Bangalore. You will build high-concurrency REST APIs using FastAPI/Flask, work with GCP networking and security, and implement scalable microservice deployments with Docker and GKE.

The role emphasizes data processing, API gateway integration, and automated testing through CI/CD pipelines, with a focus on security, observability, and cross-cloud

Qualifications

• Strong proficiency in Python for development, data processing, and automation.
• Ability to build and consume REST APIs using frameworks like FastAPI or Flask.
• Experience working with structured, semi-structured, and unstructured data.
• Hands-on experience with cloud-based application deployment and data services.
• Lead CI/CD pipelines with automated testing, secure image builds, and GitOps deployments to Kubernetes.
• Design high-performance NoSQL document schemas for high read/write workloads.
• Knowledge of SQL including complex joins, subqueries, CTEs, and window functions, PostgreSQL preferred.

Skills

Python

REST APIs

Cloud (GCP/AWS/Azure)

Data processing

Async I/O

PostgreSQL

NoSQL schemas

SQL skills

CI/CD pipelines

Networking & security

Observability

APIGateway / Apigee

API gateway

Prometheus/Grafana

Tools

Docker

Kubernetes (GKE)

Job description

Required Technical Skill Set: Cloud (GCP Preferred/AWS/Azure)

Python

Desired Experience Range: 3-8 yrs of experience

Location of Requirement: Pune, Hyderabad, Chennai, Bangalore

Must-Have

• Strong proficiency in Python for application development, data processing, and automation, Ability to build and consume REST APIs using frameworks like FastAPI or Flask.
• Experience working with structured, semi-structured, and unstructured data

Hands-on experience with cloud-based application deployment and data services

• Build high-concurrency, asynchronous REST APIs using Python and FastAPI, leveraging async/wait for non-blocking I/O and configuring CORS and middleware integrations for gateway compatibility.
• Apply deep expertise in GCP networking and security, including VPC architecture, subnet isolation, Cloud Load Balancing, IAM, Workload Identity, and resource quota and cost optimization in distributed environments.

Good-to-Have

• GCP preferred
• Configure Apigee as a centralized API gateway to act as the single-entry point for microservices, handling routing, protocol translation (REST <-> gRPC), authentication and authorization (OAuth/JWT), rate limiting, and API versioning.
• Containerize applications using efficient Dockerfiles and orchestrate deployments on Google Kubernetes Engine (GKE), including defining Pods, Services, and Ingress, implementing auto-scaling, enabling zero-downtime rolling updates, and managing service discovery
• Lead the transition from infrequent, manual monolithic releases to frequent, automated microservice deployments by designing CI/CD pipelines that support automated testing, secure Docker image builds, vulnerability scanning, and GitOps‑based deployments to Kubernetes.
• Design high-performance NoSQL document schemas optimized for high read/write workloads, enabling distributed state management without shared database bottlenecks.
• Strong knowledge of SQL including complex joins, subqueries, CTEs, and window functions.Hands-on experience with PostgreSQL or equivalent relational databases
• Author and manage complex YAML and JSON configurations across Kubernetes manifests, CI/CD pipelines, and cloud infrastructure templates, ensuring consistency, validation, linting, and version control across development, staging, and production environments.
• Enable secure cross-cloud connectivity by designing and implementing networking and security integrations (e.g., VPNs, interconnects) between GCP-based microservices and legacy Azure systems.
• Implement end-to-end observability in distributed systems by instrumenting microservices, configuring Prometheus for metrics collection, and building Grafana dashboards to monitor service health, latency, and error rates across multi-service request flows.
• Establish a unified automated testing strategy using Gherkin to bridge legacy monolithic regression suites and modern microservice-level tests.