Manager, Data Engineering Architect, AI & Data, Technology & Transformation

Overview

As a Data Engineering Architect in Deloitte’s AI & Data unit, you will design and deliver robust, scalable cloud-based data architectures and pipelines. You’ll work with diverse, cross-functional teams to address clients’ data challenges and enable data-driven decision-making. You’ll lead technical strategy, governance, and stakeholder engagement, shaping modern analytics platforms. This role offers impact across industries and opportunities to evolve with cutting-edge tech.

Pay / Benefits

• hybrid working
• flexible working arrangements
• world-class training and development
• wellbeing and supportive culture

Responsibilities

• Lead architectural assessments of existing data platforms and define target-state roadmaps using cloud IaaS/PaaS
• Evolve data engineering blueprints and pipelines for scalability and performance
• Define the technical roadmap for data platforms and enforce robust delivery via DevOps
• Provide technical leadership and mentorship to onshore/offshore engineering teams
• Evaluate and adopt emerging data technologies for strategic value and fit
• Drive the architectural vision for analytics offerings and contribute to proposals
• Provide architectural governance for client workstreams and ensure high-quality delivery
• Own and deliver one or more workstreams in client engagements

Key requirements

• Production-level development experience in Python, Scala, C++, or Java
• Cloud certification: Cloud Developer Associate, Cloud Data Engineer Associate, or similar (Architect-level preferred)
• Strong stakeholder management and ability to present to non-technical audiences
• Technical leadership and mentoring capabilities for engineering teams
• Extensive experience with cloud-based data platforms across data capture, curation, and consumption pipelines
• Experience designing data lakes, data warehouses, and related storage/compute choices
• Proficiency in data governance, data cataloguing, and data lineage concepts
• Experience with Databricks, Snowflake, and cloud services (e.g., AWS/GCP/Azure) and DevOps tools (Git, Jira, Confluence)
• Experience with data migration projects and migration strategies

• Stakeholder management
• Collaborative teamwork
• Mentorship and coaching
• Cloud platforms (Azure, AWS, GCP)
• Data engineering and pipeline development
• Data governance and cataloguing

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