Data Architect

Company Description

Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change.
 
By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses.
 
From prototype to real-world impact - be part of a global shift by doing work that matters.

Job Description

Position Summary

We are seeking a Senior Data Architect to join our North America Data & AI practice. This individual will play a key role in helping clients design and implement modern data platforms, analytics solutions, and AI-enabled architectures. The ideal candidate combines deep technical expertise with strong consulting and communication skills, enabling them to engage effectively with both technical and business stakeholders.

This role will contribute across client delivery, solution architecture, pre-sales support, proposal development, assessments, and internal capability-building initiatives. The successful candidate will be comfortable operating in both strategic advisory and hands-on architecture capacities.

Key Responsibilities

Client Delivery & Solution Architecture

• Lead architecture and design activities for data, analytics, and AI initiatives.
• Define end-to-end data platform architectures, including ingestion, storage, transformation, governance, and consumption layers.
• Develop target-state architectures, migration strategies, and modernization roadmaps.
• Conduct architecture assessments and provide recommendations aligned to business objectives.
• Collaborate with engineering teams to ensure successful implementation of architectural designs.
• Establish architecture standards, best practices, and reusable patterns.

Cloud Data Platforms

• Design and implement modern cloud-based data architectures.
• Lead architecture efforts involving Snowflake, Databricks, and major cloud platforms (AWS, Azure, and/or Google Cloud).
• Architect solutions leveraging data lakes, lakehouses, data warehouses, streaming platforms, and AI/ML services.
• Evaluate and recommend technologies based on client requirements, scalability, performance, security, and cost considerations.

Client Engagement & Consulting

• Serve as a trusted advisor to client stakeholders, including technical leaders, architects, and business executives.
• Facilitate architecture workshops, discovery sessions, and strategy discussions.
• Translate business requirements into actionable technical architectures and implementation plans.
• Present architectural recommendations and executive-level findings to client audiences.

Pre-Sales & Business Development

• Support sales pursuits through solution design, proposal development, and client presentations.
• Participate in discovery meetings, capability discussions, and architecture assessments for prospective clients.
• Contribute to estimates, statements of work, and technical responses for RFPs and proposals.
• Help shape solution offerings, accelerators, and reusable assets within the Data & AI practice.

Practice Development

• Mentor architects and engineers across the organization.
• Contribute to internal knowledge sharing, architecture standards, and technical communities of practice.
• Stay current on emerging trends in data platforms, analytics, AI, and cloud technologies.
• Support recruitment activities through interviews and technical evaluations.

Qualifications

Required Qualifications

• 12+ years of experience in data architecture, data engineering, analytics, or related disciplines.
• Proven experience designing enterprise-scale data platforms and analytics solutions.
• Strong expertise in Snowflake architecture, implementation, optimization, and best practices.
• Strong experience with Databricks, including Lakehouse architecture and modern data engineering patterns.
• Experience with at least one major cloud platform: AWS, Azure, or Google Cloud.
• Deep understanding of data warehousing, data lakes, dimensional modeling, and modern data architectures.
• Experience with ETL/ELT frameworks and data integration technologies.
• Strong understanding of data governance, security, metadata management, and data quality concepts.
• Experience leading technical teams and architecture initiatives.
• Excellent written, verbal, and presentation skills.
• Ability to c