Enterprise Technology Solution Architect

Deloitte France; United States; On-site; USD 160,000 - 210,000; Full time

Job summary

Deloitte France is seeking an experienced Enterprise Technology Solution Architect to drive architecture for complex programs, with a focus on data platforms, AI, and cloud-native solutions. You will design secure, scalable data architectures for capital markets and financial services, translate business challenges into technology outcomes, and mentor delivery teams while aligning with client roadmaps.

Join a team that enables innovation without heavy travel, delivering impact across

Qualifications

• 6+ years of experience in IT architecture, systems design, or a related technical discipline; enterprise-scale data/AI solutions.
• 6+ years with Hadoop ecosystem (preferably Cloudera) including HDFS, Hive, Pig, Sqoop, and MongoDB.
• Experience delivering AI and data architecture in Financial Services (Capital Markets, Fraud Detection, Risk Analytics, or Regulatory Reporting).
• Strong Python and PySpark skills plus Pandas, NumPy, and Pydantic; modern data architectures like Lakehouse, Medallion, Kafka, Flink, Data Mesh, OLAP/OLTP.
• Hands-on Generative AI experience: RAG pipelines, LLM integration, prompts, multi-agent workflows, vector databases (Pinecone, FAISS, Azure AI Search).
• CI/CD, Git, Docker, Kubernetes; ability to manage multiple workstreams and deliver under tight deadlines.
• Bachelor's degree in CS/IT or related IT discipline; or equivalent experience.
• Limited immigration sponsorship may be available.
• Ability to travel ~10% on average based on client work; overnight travel may be required.

Responsibilities

• Shape enterprise architecture strategies for complex technology programs, aligning solutions with client blueprints and long-term objectives.
• Design secure, scalable data platforms and AI-driven analytical solutions for capital markets and financial services organizations.
• Translate complex business challenges into innovative technology solutions that deliver measurable business outcomes.
• Develop technology roadmaps by evaluating emerging technologies, platforms, infrastructure, and AI capabilities.
• Architect advanced data pipelines and ETL solutions using Python and PySpark across relational, warehouse, and cloud-native environments.
• Design and manage distributed data processing solutions using Hadoop, Cloudera, distributed file systems, and NoSQL databases.
• Apply AI-assisted development tools, CI/CD practices, and container orchestration to improve quality and accelerate delivery.
• Serve as a senior technical advisor, mentoring development teams and governing architecture and engineering best practices across transformation programs.

Skills

Enterprise architecture

Python PySpark

Hadoop & Cloudera

Cloud platforms (AWS Azure GCP)

CI/CD & Docker Kubernetes

Data modeling & ETL

Generative AI solutions

Financial services domain

Education

Bachelor's degree in Computer Science / IT

Master's degree preferred

Tools

Hadoop (Cloudera)

MongoDB

Pandas

NumPy

Kafka

Flink

Databricks

Snowflake

Kubernetes

Docker

Job description

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Enterprise Technology Solution Architect, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. The Project Delivery Talent Model is designed for professionals with specialized skills that align to a current client need. Team members focus on delivering services to clients, without additional expectations related to business development or promotion. Their employment is tied to their role on a project, and they are eligible for a benefits package that is competitive for project delivery-focused professionals.

Work you’ll do/Responsibilities

• Shape enterprise architecture strategies for complex technology programs, aligning solutions with client blueprints and long-term objectives.
• Design secure, scalable data platforms and AI-driven analytical solutions for capital markets and financial services organizations.
• Translate complex business challenges into innovative technology solutions that deliver measurable business outcomes.
• Develop technology roadmaps by evaluating emerging technologies, platforms, infrastructure, and AI capabilities.
• Architect advanced data pipelines and ETL solutions using Python and PySpark across relational, warehouse, and cloud-native environments.
• Design and manage distributed data processing solutions using Hadoop, Cloudera, distributed file systems, and NoSQL databases.
• Apply AI-assisted development tools, CI/CD practices, and container orchestration to improve quality and accelerate delivery.
• Serve as a senior technical advisor, mentoring development teams and governing architecture and engineering best practices across transformation programs.

The Team

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You’ll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

QualificationsRequired

• 6+ years of experience in IT architecture, systems design, or a related technical discipline, with experience delivering enterprise-scale data and/or AI solutions in complex environments.
• 6+ years of experience with distributed data platforms in the Hadoop ecosystem, preferably Cloudera, including HDFS, Hive, Pig, Sqoop, and MongoDB.
• Experience delivering AI and data architecture solutions within Financial Services, particularly Capital Markets, Fraud Detection, Risk Analytics, or Regulatory Reporting.
• Strong proficiency in Python and PySpark, including Pandas, NumPy, and Pydantic, as well as modern data architectures such as Lakehouse, Medallion, Kafka, Flink, Data Mesh, and OLAP/OLTP modeling.
• Hands‑on experience designing enterprise Generative AI solutions, including RAG pipelines, LLM integration, prompt engineering, multi‑agent workflows, and vector databases such as Pinecone, FAISS, or Azure AI Search.
• Experience with CI/CD, Git, Docker, and Kubernetes, along with the organizational skills to manage multiple workstreams, take ownership of complex challenges, and deliver under tight deadlines
• Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
• Limited immigration sponsorship may be available
• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve. This may include overnight travel.

Preferred

• Master's degree in Computer Science, Data Science, Software Engineering, Mathematics, or a related quantitative discipline, and/or equivalent professional experience delivering enterprise AI and data solutions.
• Commercial & Strategic Vision: Familiarity with competitor technology products and services, with a deep understanding of how architectural specialisms contribute to commercial outcomes and Return on Investment (ROI).
• Cloud Platform & Infrastructure: Hands‑on experience designing and deploying solutions on major cloud platforms (AWS, Azure, or GCP), including cloud‑native data services (Databricks, Snowflake) and applying infrastructure engineering principles alongside software architecture.
• Project & Program Management: Experience managing and delivering complex, multi‑workstream technology programs, including stakeholder management, resource planning, and milestone governance.
• Industry Certifications: Relevant certifications such as AWS Certified Data Analytics, Google Professional Data Engineer, Databricks Certified Associate, or equivalent cloud and data architecture qualifications.