Principal Cloud & Data Architect

Seeking a Principal Cloud & Data Architect to lead architecture decisions across cloud infrastructure, Kubernetes platforms, modern data systems, and production-ready AI workloads. This is a hands-on technical leadership opportunity for an architect who can turn ambiguous requirements into workable designs, shape engagements before delivery begins, and remain accountable for what is built.

Ensure you read the information regarding this opportunity thoroughly before making an application.

You will establish reusable architecture patterns while balancing security, reliability, cost, and delivery speed.

The role combines strategic technical direction with practical engineering judgment, solution discovery, and mentorship.

About Our Client
Our client is a global technology consulting and engineering firm helping enterprises modernize their technology platforms, harness data, and adopt artificial intelligence at scale.

The company brings together expertise across cloud infrastructure, data engineering, software development, and AI to solve complex business challenges. Working with clients across multiple industries, its teams design and deliver secure, scalable, production-ready technology solutions.
With a growing focus on AI-driven transformation, the organization offers an opportunity to influence technical strategy, establish architectural standards, and help shape the next generation of enterprise technology solutions.

What you will own:
Architecture direction. Youll define reference architectures, landing zones, and standards across AWS and Azure, Kubernetes, and infrastructure-as-code. Youll decide what we standardize and what we leave flexible.

Data and AI platforms. Youll design lakehouse and warehouse, streaming, and governance patterns. Youll also design the platform layer that moves GenAI and agentic workloads from prototype to production, covering access control, evaluation, observability, and cost guardrails.

Solution shaping. Youll lead technical discovery, size and de-risk the work, and write the solution designs and technical scope that teams commit to.

AI-accelerated delivery. Youll use AI tools across the architecture lifecycle: discovery synthesis, design drafts, IaC and code generation, review, documentation, and estimation. Youll turn what works into repeatable patterns and prompts the team adopts. Youll also set the guardrails for how AI is used with client and production data.

Security and compliance by design. Youll own IAM, network segmentation, secrets management, and logging. Your designs need to hold up to SOC 2, ISO 27001, and regulated-industry scrutiny without slowing delivery down.

Cost and operability. Every design ships with a run cost, reliability targets, an observability plan, and a rollback path.

Raising the bar. Youll run design reviews, mentor architects and senior engineers, and turn repeat solutions into reusable accelerators.

What you must bring
12+ years of experience in infrastructure, cloud, or data engineering, including several years accountable for architecture of production systems at scale.
Deep hands-on experience with at least one major cloud platform: AWS or Microsoft Azure. Both are not required.
Hands-on experience with Kubernetes in production and Terraform or an equivalent infrastructure-as-code tool; ability to review implementation changes credibly.
Experience designing and delivering a modern data platform using at least one of Databricks, Snowflake, Microsoft Fabric, or Amazon Redshift, including governance and data quality.
Strong security architecture fundamentals covering IAM, zero-trust networking, encryption, and audit readiness.
Demonstrated use of AI tools to improve delivery outcomes, paired with critical review of AI-generated work before production use.
Ability to communicate architecture tradeoffs to business leaders and work directly with engineering teams to resolve technical issues.
Comfort defining an initial plan when requirements and constraints are incomplete.

What you may bring
Production experience with generative AI or LLM applications, including RAG, evaluation, guardrails, or agent orchestration.
Enterprise-scale multi-cloud or hybrid architecture experience.
Experience in regulated sectors such as financial services, healthcare, or the public sector.
AWS Solutions Architect Professional, Azure Solutions Architect Expert, or Certified Kubernetes Administrator (CKA).
Experience establishing an architecture practice or center of excellence.

Why this may excite you
Youll help define the business, not inherit it. The Cloud BU is rapidly scaling. The patterns, standards, and team habits you set now become how we operate.
The scope is broad on purpose. It covers cloud foundations, Kubernetes platforms, data, and AI workloads, so you wont be boxed into one layer.
Decisions move quickly. Youll work directly with BU leadership, and decisions take days, not quarters.
The problems are current. xmvmafu The work is getting AI workloads into production safely, building data platforms that are governed, and keeping cloud spend under control.