Data Platform Architect

Role Summary As a Senior Data Platform Architect, you’ll define the target architecture and technical roadmap for a large‑scale, hybrid data platform spanning on‑premises environments and public cloud (GCP primary, Azure secondary). You’ll set standards for DataOps, platform reliability, and automation, while mentoring engineers and partnering with security, platform, and data teams to deliver robust, compliant, and cost‑effective solutions. What You’ll Do Architecture & Strategy Own the reference architecture for a hybrid data platform. Establish patterns for data movement, storage, governance, and access controls across environments and regions. Define migration blueprints from on‑prem to cloud, including data residency, sovereignty, and hybrid operating models. Platform Engineering & Automation Build platform capabilities using Kubernetes and container orchestration for both on‑prem and cloud workloads. Implement infrastructure automation and repeatable environment provisioning with Terraform and Ansible. Design and enforce CI/CD for data pipelines (code, infra, and configuration), with automated testing and quality checks. DataOps & Reliability Introduce and scale DataOps practices: pipeline orchestration, data quality frameworks, automated validations, and lineage. Standardize tooling for orchestration (e.g., Apache Airflow, Prefect, Dagster) and promote GitOps workflows. Implement observability for data platforms using Prometheus, Grafana, ELK, Datadog, and service mesh where appropriate. Security, Compliance & Continuity Partner with security and governance to codify policy, IAM, and auditability across platform components. Design backup/restore, disaster recovery, and multi‑region strategies to meet RPO/RTO targets. Ensure compliance controls are embedded in pipelines and platform workflows. Enablement & Leadership Mentor engineers on cloud‑native design, Kubernetes internals, and infrastructure-as-code best practices. Produce living architecture docs, runbooks, and diagrams that make operating the platform simple and predictable. Continuously evaluate modern tools and approaches to improve performance, reliability, and developer experience. Minimum Qualifications Bachelor’s degree in Computer Science, Data Engineering, or a related field. 10+ years across infrastructure, DevOps, or DataOps, including platform‑level ownership. GCP (5+ years) with hands‑on expertise in BigQuery, Dataflow, Composer, GKE, Cloud Storage, IAM. Kubernetes (5+ years) in production, including Helm and service mesh (Istio or Linkerd). On‑prem experience (5+ years): bare metal, virtualization (VMware, KVM), storage systems, and networking. Orchestration experience with Airflow / Prefect / Dagster. Observability with Prometheus, Grafana, ELK, Datadog (or equivalents). CI/CD and GitOps: GitLab CI / GitHub Actions / Jenkins and GitOps workflows (e.g., Argo CD or Flux). Strong background in security, compliance frameworks, and disaster recovery planning. Infrastructure as Code at scale: Terraform, Ansible, (plus CloudFormation where applicable). Excellent communication skills; able to translate complex systems into clear decisions and stakeholder updates.