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 experiencedData Architectwith13+ yearsof experience in designing and delivering enterprise-scale cloud data platforms. The ideal candidate will possess deep expertise inAWS, Databricks, PySpark, ETL, Delta Live Tables (DLT), and modern Lakehouse architectures, along with strong experience inGenerative 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 withglobal banking and financial services organizationssuch asJPMorgan Chase, Citi, Wells Fargo, or similaris highly preferred.

Key Responsibilities

• Enterprise Data Architecture
• Design and implement enterprise-scale cloud-native data platforms usingAWS, Databricks, and PySpark.
• Architect modernLakehousesolutions 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 ofGenerative AIandAgentic AIsolutions aligned with business objectives.
• Design enterprise AI architectures leveragingLarge 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 usingPySpark,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+ yearsof experience in Data Engineering, Data Architecture, or Cloud Data Platforms.
• Strong hands-on expertise withAWS, Databricks, PySpark, ETL, and Delta Live Tables (DLT).
• Deep understanding ofLakehouse Architecture, enterprise data platforms, and cloud-native solutions.
• Experience designing enterprise-scale data processing and analytics platforms.
• Strong experience inGenerative 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 asJPMorgan 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.