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





- Solid 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.

Technical Skills

Cloud Platform

- Google Cloud Platform (GCP)

GCP Data Services

- Dataproc
- BigQuery
- Dataform
- Cloud Composer
- GCS
- Dataflow
- Bigtable
- Spanner

CI/CD & Automation

- GitLab
- GitLab CI/CD
- Pipeline templates
- Deployment automation
- Environment promotion workflows

Programming

- Python
- Go

Data Engineering

- Data pipeline design
- Batch processing
- Streaming workloads
- Orchestration frameworks

Platform Engineering

- Reusable tooling
- Automation frameworks
- Developer enablement
- Self-service platforms

DevOps Practices

- Version control
- Release workflows
- Automated validation
- CI/CD governance

Deutsche Telekom is one of the world's leading integrated telecommunications companies, with some 252 million mobile customers, 25 million fixed-network lines, and 22 million broadband lines. Deutsche Telekom is present in more than 50 countries. With a staff of some 200,000 (Dec 31, 2023) employees throughout the world, we generated revenue of 111,9 billion Euros in the 2023 financial year. As of 2023, It is rated as the 9th most valuable brand in the world.

Deutsche Telekom Digital Labs is the digital powerhouse that fuels Deutsche Telekom’s vision to be a “Leading Digital Telco”. We create compelling digital propositions for the worlds’ largest Telekom giant by building scalable, agile and innovative platforms to provide the best of digital experience to Deutsche Telekom customers across Europe and US.

📌 DevOps Engineer-II (Gurugram)
🏢 Deutsche Telekom Digital Labs
📍 Gurugram