Data Architect C2C requirements AWS, Databricks & Generative AI

Job Title: Data Architect – AWS, Databricks & Generative AI

Dallas, Texas – Onsite

Duration: Contact   – client – Virtusa

Job Summary
We are seeking an experienced Data Architect with 13+ years of experience in designing and delivering enterprise-scale cloud data platforms. The ideal candidate will possess deep expertise in AWS, Databricks, PySpark, ETL, Delta Live Tables (DLT), and modern Lakehouse architectures, along with strong experience in Generative AI, Large Language Models (LLMs), and Agentic AI.
The role requires a strategic technical leader capable of defining enterprise architecture, driving client-facing solution discussions, mentoring engineering teams, and delivering secure, scalable, and high-performance data platforms. Experience working with global banking and financial services organizations such as JPMorgan Chase, Citi, Wells Fargo, or similar is highly preferred.

Key Responsibilities
Enterprise Data Architecture
Design and implement enterprise-scale cloud-native data platforms using AWS, Databricks, and PySpark.
Architect modern Lakehouse solutions for analytics and AI workloads.
Define enterprise data architecture standards, frameworks, and best practices.
Design scalable, secure, and high-performance data processing solutions.
AI & Intelligent Data Solutions
Lead the architecture and implementation of Generative AI and Agentic AI solutions aligned with business objectives.
Design enterprise AI architectures leveraging Large Language Models (LLMs), AI Agents, and orchestration frameworks.
Collaborate with AI engineering teams to integrate AI capabilities into enterprise data platforms.
Ensure AI solutions meet enterprise security, governance, and scalability requirements.
Data Engineering & Platform Development
Lead development of high-performance data pipelines using PySpark, ETL, and Delta Live Tables (DLT).
Optimize data ingestion, transformation, orchestration, and processing pipelines.
Define reusable frameworks for enterprise data engineering.
Improve performance, scalability, reliability, and cost efficiency of data workloads.
Architecture & Technical Leadership
Drive architecture discussions, technical strategy, and solution design with clients and internal stakeholders.
Lead solution reviews, architecture walkthroughs, and technical governance sessions.
Define coding standards, engineering practices, and architecture principles.
Mentor engineering teams and promote engineering excellence.
Client & Stakeholder Management
Gather and analyze client business requirements.
Translate business needs into scalable technical architectures.
Present architecture proposals and solution roadmaps to executive stakeholders.
Build trusted relationships with business and technology leadership.
Governance & Security
Ensure compliance with enterprise security, governance, and data management standards.
Implement secure cloud architecture and data governance best practices.
Establish data quality, lineage, and metadata management processes.
Support regulatory and compliance requirements for enterprise platforms.
Agile Delivery
Collaborate with Product Managers, Engineering Managers, Scrum Masters, and Technical Leads.
Support sprint planning, technical estimation, and milestone delivery.
Resolve complex architectural and engineering challenges.
Drive continuous improvement across engineering teams.

Required Technical Skills
Cloud Platform
Amazon Web Services (AWS)
Cloud Data Architecture
Cloud-Native Solutions
Data Engineering
Databricks
PySpark
ETL
Delta Live Tables (DLT)
Data Pipelines
Data Orchestration
Data Modeling
Pipeline Optimization
Modern Data Platforms
Lakehouse Architecture
Data Lake
Data Warehouse
Enterprise Data Platforms
Artificial Intelligence
Generative AI
Agentic AI
Large Language Models (LLMs)
AI Agents
AI Orchestration Frameworks
Prompt Engineering (Preferred)
Retrieval-Augmented Generation (RAG) (Preferred)
Architecture
Solution Architecture
Enterprise Architecture
Technical Leadership
Architecture Governance
Technical Strategy
Delivery
Agile
Scrum
SDLC
DevOps (Preferred)
Banking Domain (Preferred)
Banking & Financial Services
Enterprise Banking Platforms
Regulatory Compliance

Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, Data Engineering, Artificial Intelligence, or a related field.
13+ years of experience in Data Engineering, Data Architecture, or Cloud Data Platforms.
Strong hands-on expertise with AWS, Databricks, PySpark, ETL, and Delta Live Tables (DLT).
Deep understanding of Lakehouse Architecture, enterprise data platforms, and cloud-native solutions.
Experience designing enterprise-scale data processing and analytics platforms.
Strong experience in Generative AI, Large Language Models (LLMs), AI Agents, and orchestration frameworks.
Proven ability to lead architecture discussions, technical solutioning, and client engagements.
Experience mentoring engineering teams and driving technical excellence.
Strong communication, presentation, and stakeholder management skills.
Experience working within Agile development environments.

Preferred Qualifications
AWS Certified Solutions Architect – Professional
Databricks Certified Data Engineer or Databricks Architect Certification
TOGAF Certification
Experience with global banking organizations such as JPMorgan Chase, Citi, Wells Fargo, or equivalent financial institutions.
Experience with ML platforms, MLOps, or AI platform engineering.
Knowledge of Infrastructure as Code (Terraform or CloudFormation).

Primary Skills
AWS
Databricks
PySpark
ETL
Delta Live Tables (DLT)
Lakehouse Architecture
Data Architecture
Data Modeling
Data Pipelines
Pipeline Optimization
Generative AI
Large Language Models (LLMs)
Agentic AI
AI Agents
Solution Architecture
Technical Leadership
Secondary Skills
TOGAF
AWS Solutions Architect
Databricks Certification
Terraform
CloudFormation
Prompt Engineering
Retrieval-Augmented Generation (RAG)
MLOps
DevOps
Agile
Scrum
Banking Domain

Soft Skills
Excellent leadership and mentoring abilities.
Strong client-facing communication and presentation skills.
Strategic thinking with strong solution design capabilities.
Outstanding analytical and problem-solving skills.
Ability to influence stakeholders and drive architectural decisions.
Strong collaboration and cross-functional leadership.
Commitment to engineering excellence and continuous improvement.