About the role
AI summarisedManager-level Solution Architect role at Deloitte's A&A practice, focusing on designing end-to-end data, analytics, and AI solutions for investment management clients. The role involves architectural leadership, stakeholder engagement, technical solutioning, and delivery oversight, requiring deep expertise in Databricks, Microsoft Fabric, and cloud platforms.
BusinessFull-timeAssurance
Key Responsibilities
- Design and lead end-to-end architecture for data, analytics, and AI solutions across the investment management ecosystem.
- Develop scalable, secure, and governed data warehouse and data lakehouse architectures using Databricks and Microsoft Fabric.
- Define integration patterns, data pipelines, processing frameworks, and consumption layers for enterprise‑grade systems.
- Evaluate and align architectural decisions with business strategy, regulatory requirements, and technology roadmap.
- Craft compelling narratives that explain technical concepts, solution designs, and implementation roadmaps to both technical and non-technical audiences.
- Translate complex architectures into intuitive visuals, models, and presentations.
- Lead architecture workshops, executive briefings, and technical deep dives.
- Influence cross-functional teams, ensuring alignment and buy‑in across business, data, and engineering stakeholders.
- Apply advanced knowledge of data warehousing, data modeling, metadata management, data governance, and data quality frameworks.
- Guide the adoption and integration of modern AI technologies, including Gemini AI, into data and analytics workflows.
- Oversee solution feasibility, scalability assessments, and performance optimization.
- Ensure best practices related to security, privacy, compliance, and cloud architecture.
Requirements
- Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field.
- Proven experience (10+ years) in solution architecture, data architecture, or enterprise architecture.
- Strong experience in investment management or broader financial services data domains.
- Hands-on expertise with Databricks (Delta Lake, Unity Catalog, PySpark, MLflow).
- Hands-on expertise with Microsoft Fabric (OneLake, Data Engineering, Data Science, Power BI).
- Hands-on expertise with Cloud platforms (Azure preferred).
- Hands-on expertise with AI/ML platforms, including Gemini AI or similar LLM ecosystems.
- Strong knowledge of data warehousing, data modeling, ETL/ELT frameworks, and analytical workloads.
- Exceptional storytelling, communication, and stakeholder engagement skills.
- Demonstrated ability to lead cross-functional teams and deliver enterprise-grade solutions.
- Preferred: Experience with portfolio management, trading systems, investment operations, or risk & performance data.
- Preferred: Certifications in Azure, Databricks, TOGAF, or similar architecture frameworks.
- Preferred: Experience with modern data governance platforms and lineage tools.