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Global digital transformation solutions provider.
Job Description
We are seeking a highly skilled Site Reliability Engineer (SRE) with strong expertise in Google Cloud Platform (GCP) and CI/CD automation to lead cloud infrastructure initiatives. The ideal candidate will design and implement robust CI/CD pipelines, automate deployments, ensure platform reliability, and drive continuous improvement in cloud operations and DevOps practices.
Key Responsibilities:
- Design, develop, and optimize end-to-end CI/CD pipelines using Jenkins, with a strong focus on Declarative Pipeline syntax.
- Automate deployment, scaling, and management of applications across various GCP services including GKE, Cloud Run, Compute Engine, Cloud SQL, Cloud Storage, VPC, and Cloud Functions.
- Collaborate closely with development and DevOps teams to ensure seamless integration of applications into the CI/CD pipeline and GCP environment.
- Implement and manage monitoring, logging, and ing solutions to maintain visibility, reliability, and performance of cloud infrastructure and applications.
- Ensure compliance with security best practices and organizational policies across GCP environments.
- Document processes, configurations, and architectural decisions to maintain operational transparency.
- Stay updated with the latest GCP services, DevOps, and SRE best practices to enhance infrastructure efficiency and reliability.
Mandatory Skills:
- Google Cloud Platform (GCP) – Hands-on experience with core GCP compute, networking, and storage services.
- Jenkins – Expertise in Declarative Pipeline creation and optimization.
- CI/CD – Strong understanding of automated build, test, and deployment workflows.
- Solid understanding of SRE principles including automation, scalability, observability, and system reliability.
- Familiarity with containerization and orchestration tools (Docker, Kubernetes – GKE).
- Proficiency in scripting languages such as Shell, Python, or Groovy for automation tasks.
Preferred Skills:
- Experience with Terraform, Ansible, or Cloud Deployment Manager for Infrastructure as Code (IaC).
- Exposure to monitoring and observability tools like Stackdriver, Prometheus, or Grafana.
- Knowledge of multi-cloud or hybrid environments (AWS experience is a plus).
- GCP certification (Professional Cloud DevOps Engineer / Cloud Architect) preferred.
Skills
Gcp, Jenkins, CICD Aws,
Nice to Haves
Experience with Terraform, Ansible, or Cloud Deployment Manager for Infrastructure as Code (IaC).
Exposure to monitoring and observability tools like Stackdriver, Prometheus, or Grafana.
Knowledge of multi-cloud or hybrid environments (AWS experience is a plus).
GCP certification (Professional Cloud DevOps Engineer / Cloud Architect) preferred.
******
Notice period - 0 to 15days only
Location – Pune, Trivandrum, Kochi, Chennai
InViz is Bangalore Based Startup helping Enterprises simplifying the Search and Discovery experiences for both their end customers as well as their internal users. We use state-of-the-art technologies in Computer Vision, Natural Language Processing, Text Mining, and other ML techniques to extract information/concepts from data of different formats- text, images, videos and make them easily discoverable through simple human-friendly touchpoints.
TSDE - Data
Data Engineer:
- Should have total 3-6 Yrs of experience in Data Engineering.
- Person should have experience in coding data pipeline on GCP.
- Prior experience on Hadoop systems is ideal as candidate may not have total GCP experience.
- Strong on programming languages like Scala, Python, Java.
- Good understanding of various data storage formats and it’s advantages.
- Should have exposure on GCP tools to develop end to end data pipeline for various scenarios (including ingesting data from traditional data bases as well as integration of API based data sources).
- Should have Business mindset to understand data and how it will be used for BI and Analytics purposes.
- Data Engineer Certification preferred
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Experience in Working with GCP tools like |
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Store : CloudSQL , Cloud Storage, Cloud Bigtable, Bigquery, Cloud Spanner, Cloud DataStore |
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Ingest : Stackdriver, Pub/Sub, AppEngine, Kubernete Engine, Kafka, DataPrep , Micro services |
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Schedule : Cloud Composer |
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Processing: Cloud Dataproc, Cloud Dataflow, Cloud Dataprep |
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CI/CD - Bitbucket+Jenkinjs / Gitlab |
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Atlassian Suite |
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