Data Architect – Manager – AI & Data at Deloitte

Job Description

• We are hiring a Data Architect with demonstrated leadership in designing and delivering modern data architectures and enabling AI and ML at scale. This role requires deep technical architecture expertise, strong delivery management capability, and the ability to engage with C-level stakeholders on data and AI transformation programs.
• You will shape and lead multi-market programs that enable clients across industries to build cloud-native data platforms, accelerate AI adoption, and scale data-driven business value.

Key responsibilities

Client leadership & Advisory

• Act as technical advisor to client CIOs, CDOs, and CAIOs on data platform modernisation
• Facilitate solution workshops and blueprinting sessions with executive and technical stakeholders
• Translate business problems into scalable data architectures
• Serve as a trusted advisor to clients on data modernization, AI readiness, and cloud data strategy
• Drive discovery workshops, blueprinting sessions, and technical architecture reviews
• Lead client engagements with agile delivery methods and engineering excellence

Architecture ownership

• Lead the design of cloud-native data architectures (Lakehouse, Data Mesh, Real-time)
• Own end-to-end architecture and governance: ingestion, transformation, storage, security
• Align data platform strategy with AI and analytics enablement (e.g., MLOps, model serving)
• Architect end-to-end data pipelines (batch, real-time) using modern tools (e.g., Spark, Kafka, dbt, Airflow)
• Build and optimize data platforms that support AI/ML workloads, model deployment, and monitoring

Delivery & Quality assurance

• Manage teams delivering high-performance data pipelines and platform foundations
• Implement data quality, lineage, privacy, and governance frameworks at scale
• Own technical quality, delivery velocity, and stakeholder satisfaction
• Own the design and implementation of robust data ingestion, transformation, and governance processes
• Guide teams on data quality, lineage, metadata management, and data security best practices
• Collaborate closely with data scientists to operationalize ML models via MLOps best practices

Team leadership & Growth

• Lead and mentor cross-functional engineering teams (onshore/offshore)
• Mentor junior data engineers and consultants, promoting engineering standards and technical excellence
• Contribute to internal capability building and innovation within the AI & Data practice
• Influence recruitment decisions and grow capability in data engineering & architecture
• Coach client teams and promote engineering best practices

Qualifications
Cloud Platforms:

• Azure, AWS, or GCP (deep expertise in at least one)

Data Tools:

• Spark, Databricks, Snowflake, BigQuery, Redshift, Delta Lake

Pipelines & Orchestration:

• Airflow, dbt, Kafka, NiFi, Glue, Synapse

Programming:

• Python (mandatory), SQL (expert), Scala/Java (bonus)

MLOps/AI Enablement:

• Model serving, feature stores, MLflow, Vertex.ai, SageMaker

Architecture Patterns:

• Data Mesh, Lakehouse, Streaming Analytics, CDC

Consulting experience:

• Prior experience in top-tier or boutique consulting preferred
• Client facing professional services roles with Enterprise software providers also preferred
• Ability to operate in ambiguity, structure complex challenges, and deliver value rapidly