Site Reliability Engineer

LEE GARRETT ENTERPRISES.LLC

United States

5 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

computerjobs.com

Tech stack

Airflow Amazon Web Services Amazon Elastic Compute Cloud Amazon S3 Bash Shell BigQuery Cloud Computing Cloud Storage Continuous Integration Data Architecture Information Engineering Data Infrastructure

+26 more

Data Visualization Data Flow Control Github Identity and Access Management Interoperability Python (Programming Language) Network Security Operational Databases Reliability Engineering Power BI Tableau (Software) Alwayson Qliksense Scripting Google Cloud Grafana HybridCloud Infrastructure as Code (IaC) Amazon Virtual Private Cloud (VPC) Gitlab-ci Kubernetes Qlikview Data Lakehouse Terraform Devsecops Microservices

Job description

We’re looking for a Site Reliability Engineer to take ownership of our Google Cloud environment and make sure the data platform stays fast, available, and cost-efficient as it scales.

What You Will Do

Kubernetes Orchestration Own and manage Google Kubernetes Engine (GKE) clusters, including advanced networking (VPC Service Controls, Shared VPC) and high-availability node configurations to keep production data platforms resilient and always-on.
Data Architecture (Lakehouse) Design and support a unified Data Lakehouse architecture integrating BigQuery and Cloud Storage. Implement governance and security policies to ensure data quality, accessibility, and cost-efficiency across a single source of truth.
Infrastructure as Code (IaC) Use Terraform to automate the life cycle of GCP resources (Compute Engine, Cloud Run, Cloud SQL), maintaining consistency and reducing configuration drift across Dev, Staging, and Production environments.
BI/Data Visualization Support Deploy, optimize, and scale enterprise visualization tools (Tableau, Qlik Sense, or similar) on GCP, including SSO/IAM authentication and Back End connectivity.
Hybrid Cloud & Legacy Modernization Manage AWS resources (EC2, S3) alongside GCP, ensuring interoperability. Lead migration of Legacy monolithic systems to microservices-based architectures.
Data Engineering Collaboration Work with Data Engineers to build and maintain pipelines using Cloud Dataflow, Cloud Composer (Airflow), and BigQuery.
Reliability, Security & FinOps. CI/CD: Design pipelines (GitLab CI/GitHub Actions) with DevSecOps practices. Observability: Implement deep monitoring, alerting, and SLIs/SLOs using Google Cloud Operations Suite and Grafana. FinOps: Identify and reduce cloud cost waste

Requirements

Proven experience managing complex environments in GCP and AWS
Strong understanding of Data Lakehouse models and governance
Deep knowledge of GKE, including advanced networking and security policies
Ability to write modular, scalable, secure Terraform code
Experience deploying and tuning enterprise visualization tools (Tableau, Qlik, or Power BI)
Strong Scripting skills (Python, Bash, or Go) and CI/CD experience
Familiarity with Airflow, BigQuery, and Dataflow
Solid understanding of encryption, IAM roles, and network security standards