Google Data Architect

About the Role Google Data Architect within Slalom's Google COE, focusing on building and modernizing data platforms on Google Cloud. You will design and deliver enterprise-scale data platforms on GCP and guide clients through migration, real-time and batch data pipelines, and AI-ready data foundations. You will collaborate with client teams and Slalom colleagues to translate business needs into scalable cloud data solutions. What You'll Do

• Design and deliver enterprise-scale data platforms on Google Cloud Platform (GCP).
• Architect solutions using BigQuery, Dataplex, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Vertex AI, Looker, Cloud Composer, and other Google Cloud services.
• Help clients migrate and modernize data estates, implement real-time and batch data platforms, enable governed analytics, and accelerate AI-ready data foundations.
• Understand the client's current environment, business outcomes, and future-state data strategy; lead analysis, architecture, design, and delivery of the next-generation Google Cloud Data Platform solution.
• Communicate trade-offs, benefits, risks, and implementation path; drive consensus between Slalom and client teams.
• Break down complex architectures into deliverable workstreams and ensure quality completion of development items.
• Participate in pre-sales activities as time allows, shaping data modernization approaches, defining solution options, supporting estimates and delivery plans, and partnering with business development.
• Maintain hybrid working arrangements and be within commutable distance to listed Slalom office locations. What We're Looking For
• Broad architecture experience with deep expertise in Google Cloud data engineering technologies.
• Curious mindset to client engagements; hunger for fearless experimentation.
• Self-starter, able to break down large problems into smaller parts and share learnings with teams.
• Passion for Google Cloud and modern data architecture; ongoing learning through delivery, certifications, and collaboration.
• Excellent communication and mentoring skills; ability to describe trade-offs and decisions.
• Experience delivering on Google Cloud data platform projects; knowledge of GCP services listed. Nice to Have
• Google Cloud Professional Data Engineer certification.
• Google Cloud Professional Cloud Architect certification.
• Looker, Looker Studio, semantic modeling.
• Gemini Enterprise, Vertex AI, MLOps, and AI-enabled data architecture.
• Experience migrating from AWS, Azure, Teradata, Hadoop, Informatica, Snowflake, or legacy data platforms to Google Cloud.