Data Architect C2C requirements AWS, Databricks & Generative AI

Tech Mirrors

Dallas (TX)

On-site

USD 140,000 - 180,000

Full time

14 days+

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Job summary

Tech Mirrors in Dallas, TX is seeking an experience Data Architect to design enterprise-scale cloud data platforms using AWS, Databricks, and PySpark. You will lead data architecture decisions, mentor teams, and guide secure, scalable implementations for high-performance analytics and AI workloads.

The role emphasizes Generative AI, LLMs, and AI Agents, with a focus on governance, security, and collaboration with stakeholders across banking and financial services.

Qualifications

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 and enterprise data platforms.

Responsibilities

Design and implement enterprise-scale cloud-native data platforms on AWS and Databricks.
Lead architecture discussions, client engagements, and solution reviews.
Mentor engineering teams and enforce governance, security, and best practices.
Drive AI-enabled data solutions using Generative AI, LLMs, and AI Agents.

Skills

Enterprise Data Architecture

Technical Leadership

Strategic Solution Design

Agile / Scrum

Client Engagement

Education

Bachelor’s or Master’s in Computer Science or related field

Tools

AWS

Databricks

PySpark

ETL

Delta Live Tables (DLT)

Lakehouse Architecture

AI / Generative AI

LLMs

AI Agents

AI Orchestration Frameworks

Job description

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