Consultant GCP DevOps Engineer

Tredence; Pune District, Chennai, Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Tredence Inc. is seeking a GCP DevOps / DataOps Engineer to design, automate, and maintain cloud infrastructure and data pipelines.

You will collaborate with GCP Data Engineers, Analytics Consultants, and client IT teams to build secure, production-grade pipelines for ingesting, cleaning, and modeling marketing and membership data across various channels. The role emphasizes IaC design with Terraform, data workflow automation using BigQuery, Cloud Composer, dbt, and Dataflow, plus strong

Qualifications

• 4+ years in DevOps/SRE with at least 3+ years on Google Cloud Platform (GCP).
• IaC expertise in Terraform with modular design and drift detection.
• Operationalizing data stacks on GCP (BigQuery, Cloud Composer, dbt, Dataflow).
• Experience with CI/CD pipelines across GitHub Actions, GitLab CI, or Cloud Build.

Responsibilities

• Design, provision, and maintain modular GCP resources using Terraform.
• Build automated CI/CD pipelines for data workflows (BigQuery, Airflow, dbt, Dataflow).
• Implement least-privilege IAM, service accounts, and data security standards.
• Establish end-to-end monitoring and alerting across ingestion pipelines and analytics stores.
• Collaborate with client IT/platform teams for firewall rules and private connectivity.
• Monitor costs and performance across GCP compute and analytics engines.

Skills

DevOps experience

GCP experience

CI/CD practices

Scripting (Python/Bash)

Tools

Terraform

BigQuery

Cloud Composer (Airflow)

dbt

Cloud Dataflow

GitHub Actions

GitLab CI

Cloud Build

Cloud Monitoring

Cloud Logging

Slack/Teams notifications

Python

Bash

Docker

Artifact Registry

GCP IAM / Service Accounts

Job description

Job Description: GCP DevOps / DataOps Engineer

Role Overview

We are looking for a GCP DevOps / DataOps Engineer to design, automate, and maintain the cloud infrastructure . In this role, you will work hand-in-hand with GCP Data Engineers, Analytics Consultants, and the clients central IT/platform teams to build automated, secure, and production-grade pipelines that ingest, clean, and model marketing and membership data across diverse acquisition and retention vehicles.

Key Responsibilities

• Infrastructure as Code (IaC): Design, provision, and maintain modular GCP cloud resources using Terraform, ensuring environment parity across Dev, Staging, and Production.
• DataOps CI/CD Pipelines: Build automated CI/CD pipelines (GitHub Actions / GitLab CI / Cloud Build) for data workflows, including BigQuery, Cloud Composer (Airflow), dbt, and Cloud Dataflow.
• Security & Compliance: Implement least-privilege IAM, service account management, customer data security standards, VPC service controls, and encryption (KMS) aligned with US retail data governance.
• Observability & Reliability: Establish end-to-end monitoring, automated alerting, and log routing across ingestion pipelines and analytical databases using Cloud Monitoring, Cloud Logging, and custom Slack/Teams notifications.
• Cost Optimization & Performance: Partner with Data Engineering to monitor query costs, storage tiers, auto-scaling thresholds, and resource utilization across GCP compute and analytics engines.
• Client & Stakeholder Collaboration: Coordinate with client platform engineering and infosec teams to navigate firewall rules, private connectivity, and compliance approvals.

Required Qualifications & Skills

• Experience: 4+ years in DevOps/SRE, with at least 3+ years dedicated to Google Cloud Platform (GCP).
• IaC & Automation: Strong expertise in Terraform (writing reusable modules, state management in GCS, automated drift detection).
• Data & Analytics Stack: Practical experience operationalizing data stacks on GCP:
• Google BigQuery (partitioning, clustering, slot management, CI/CD for schema migrations/dbt).
• Cloud Composer / Apache Airflow (DAG deployment automation, dependency management).
• Cloud Storage, Pub/Sub, and Dataflow/Dataproc.
• CI/CD Mastery: Deep hands-on experience building multi-stage deployment pipelines (GitHub Actions, GitLab CI, or Cloud Build) with automated testing, linting, and security scanning (SonarQube, Trivy, or Snyk).
• Scripting & Containers: Proficiency in Python and Bash; strong command of Docker containerization and container registry management (Artifact Registry).
• Networking & Security: Solid understanding of GCP VPCs, Private Google Access, Cloud NAT, IAM policies, and Service Accounts.

Preferred / Nice-to-Have

• GCP Professional Cloud DevOps Engineer or Professional Google Cloud Architect certification.
• Experience in retail media, loyalty programs, or ad-tech data environments handling high-volume transaction/clickstream datasets.
• Exposure to MLOps tools (Vertex AI pipelines, feature stores, model registry