DevOps Engineer-II

deutsche telekom digital labs

Fresher

Not Disclosed

Gurugram, India, Gurugram

Early Applicant

Posted 19 days ago
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Job Description

Platform Engineering | Google Cloud | Data & AI Enablement

We are looking for a Senior Developer to help build and evolve the CI/CD frameworks used by our Data and AI Platform teams.

This role is focused on building reusable platform capabilities rather than one-off project-specific implementations. You will work closely with data engineers, AI/ML engineers, and platform teams to design reusable pipelines, automation frameworks, deployment patterns, and self-service engineering capabilities for modern data and AI workloads on Google Cloud Platform.

The right person for this role is hands-on, comfortable writing production-quality code, and has a strong understanding of both cloud services and CI/CD engineering practices. You should be able to take complex platform requirements and turn them into scalable, reusable frameworks that engineering teams can easily adopt.

Key Responsibilities

Build Platform CI/CD Frameworks

Design and develop reusable GitLab CI/CD frameworks for Data and AI platform teams.
Create reusable pipeline templates, deployment workflows, validation steps, and automation standards that can be adopted across projects and environments.
Build self-service deployment capabilities and golden-path engineering workflows for Data & AI teams.

Enable GCP Data Platform Deployments

Build deployment patterns and automation for core GCP data services including:

Dataproc
BigQuery
Dataform
Cloud Composer
Google Cloud Storage
Dataflow
Bigtable
Cloud Spanner

Enable teams to deploy, configure, and operate these services through reliable and repeatable CI/CD processes.
Design frameworks supporting multi-environment and multi-tenant deployment patterns.

Support Data Pipeline Delivery

Design CI/CD workflows for:

Batch data pipelines
Streaming workloads
Transformation logic
Orchestration workflows
Environment-specific releases

Work with engineering teams to improve how data pipelines are built, tested, promoted, and deployed across environments.

Develop Internal Tools and Automation

Build platform tools, APIs, CLIs, scripts, and reusable libraries using Python and Go.
Focus on reducing repetitive work, improving developer experience, and making platform capabilities easier for teams to adopt.
Apply software engineering best practices including testing, modular design, versioning, and maintainability to platform tooling and frameworks.

Partner with Engineering Teams

Work closely with data, AI, platform, and infrastructure teams to understand engineering challenges and convert them into scalable platform solutions.
Help define practical standards for:

Pipeline design
Deployment automation
Release management
Operational readiness
CI/CD governance

Must-Have Qualifications

Strong experience designing and building CI/CD frameworks for platform or engineering teams.
Expert-level knowledge of Google Cloud Platform and hands-on experience with GCP data services.
Deep experience with:

Dataproc
BigQuery
Dataform
Cloud Composer
GCS
Dataflow
Bigtable
Spanner

Strong experience with GitLab and GitLab CI/CD pipeline design.
Experience designing CI/CD pipelines for data platforms, analytics workloads, or AI/ML platform teams.
Strong understanding of data pipeline design including:

Batch processing
Streaming architectures
Orchestration
Transformation workflows
Environment promotion

Strong application development experience with Python.
Hands-on development experience with Go.
Ability to build reusable frameworks, deployment templates, automation utilities, and engineering standards.
Experience working with cross-functional engineering teams in platform, DevOps, or cloud engineering environments.