Data Architect with GCP contract role Direct client

Tech Mirrors; Atlanta (GA); Hybrid; USD 140,000 - 165,000; Full time

Job summary

Tech Mirrors is seeking a Strategic & Architectural Leader to define AI & data architecture strategy and roadmaps. You will guide modern data, analytics, and GenAI architectures, and partner with leaders to prioritize high-impact AI use cases.

You will lead end-to-end designs for scalable data platforms across GCP, AWS, and Snowflake, with emphasis on governance and cost efficiency. The role requires deep cloud data experience, strong leadership, and the ability to communicate complex concepts

Qualifications

• 14+ years of hands-on experience in data architecture, analytics solutions, and cloud data platforms.
• 3+ years delivering AI/ML and Generative AI solutions in production.
• 6+ years designing and scaling enterprise data platforms on GCP, AWS, and Snowflake.
• Bachelor’s Degree in Engineering or related technical discipline.

Responsibilities

• Define and evolve AI & Data architecture strategy and roadmap aligned with priorities.
• Serve as thought leader for data, analytics, and AI architectures including GenAI.
• Lead end-to-end architecture design for data/analytics/AI initiatives with scalability and security.
• Design cloud-based data platforms on GCP, AWS, Snowflake and govern related patterns.
• Establish MLOps/LLMOps frameworks and ensure model observability and governance.
• Provide technical leadership and mentorship to architects, engineers, and scientists.

Skills

Data architecture

Architectural thinking

Leadership & mentoring

Communication skills

Stakeholder management

Self-driven

Education

Bachelor's Degree in Engineering

Master's degree or Ph.D. preferred

Tools

GCP

AWS

Snowflake

Python

SQL

PySpark

TensorFlow

PyTorch

Kubernetes

Docker

CI/CD

Data Lake / Lakehouse

Job description

Contract

Atlanta, GA (Hybrid)

Rate: $70/hr on C2C (Max)

Job Description

Strategic & Architectural Leadership

• Define and evolve AI & Data architecture strategy and roadmap, aligned with business priorities and IT strategy.
• Serve as a thought leader for modern data, analytics, and AI architectures, including Generative AI and Agentic AI.
• Identify, evaluate, and recommend emerging technologies, platforms, and architectural patterns.
• Partner with business and digital leaders to identify and prioritize high-impact AI and analytics use cases.
• Provide architectural guidance on ethical, responsible, and compliant AI adoption.

Solution Architecture & Platform Design

• Lead end-to-end architecture design for complex data, analytics, and AI initiatives, ensuring scalability, performance, security, and cost efficiency.
• Design and govern cloud-based data platforms leveraging:
• Google Cloud Platform (BigQuery, Vertex AI, Dataflow, Dataproc, Looker)
• AWS (S3, Glue, EMR, Redshift, SageMaker, Lambda)
• Snowflake (data warehouse, data sharing, performance optimization)
• Architect modern enterprise data architectures, including:
• Data Lake, Lakehouse, Data Mesh, and Data Fabric
• Open table/file formats such as Parquet, Iceberg, Delta Lake
• Medallion architectures (Bronze/Silver/Gold)
• Define data ingestion and integration patterns across structured and semi-structured sources (SAP, Oracle, Salesforce, JDE, Ariba, IoT, APIs, NoSQL).
• Define and enforce data quality, metadata, lineage, and access control standards.

AI, ML, and Generative AI Architecture

• Design and implement AI/ML and GenAI solution architectures from experimentation through production.
• Architect solutions for core ML use cases such as demand forecasting, predictive maintenance, supply chain optimization, and customer analytics.
• Lead architecture for Generative AI and Agentic AI, including:
• LLM integration with tools, APIs, and knowledge bases (RAG patterns)
• Autonomous and semi-autonomous agent workflows
• Fine-tuning, prompt engineering, and optimization strategies
• Establish MLOps and LLMOps frameworks for model training, deployment, monitoring, evaluation, and lifecycle management.
• Define approaches for model observability, explainability (XAI), bias detection, and risk mitigation.

Technical Leadership & Collaboration

• Provide technical leadership and mentorship to solution architects, data engineers, data scientists, and AI engineers.
• Collaborate closely with platform, DevOps, and cloud engineering teams to enable automation-driven deployments.
• Review solution designs, conduct architecture assessments, and provide impact analysis and recommendations.
• Communicate complex technical concepts clearly to both technical and executive audiences.

Required Qualifications

• Bachelor’s Degree in Engineering or a related technical discipline.
• 14+ years of hands-on experience in data architecture, analytics solutions, and/or cloud data platforms.
• 3+ years of hands-on experience delivering AI/ML and Generative AI solutions in production.
• 6+ years of experience designing and scaling enterprise data platforms on GCP, AWS, and Snowflake.

Preferred Qualifications

• Master’s degree or Ph.D. preferred.
• Demonstrated success leading large-scale, cross-functional data and AI initiatives.
• Cloud platforms: GCP and AWS (multi-cloud experience strongly preferred)
• Data platforms: Snowflake, BigQuery, Data Lakes, Lakehouse architectures
• Programming & analytics: Python, SQL, PySpark
• AI/ML frameworks: TensorFlow, PyTorch, scikit-learn, XGBoost
• GenAI/LLM frameworks, vector databases, and graph databases
• Data engineering tools: Spark, Kafka, Hadoop
• Containerization and orchestration: Docker, Kubernetes
• CI/CD and DevOps practices
• Strong understanding of data modeling, performance tuning, and cost optimization
• Strong architectural thinking and problem-solving skills
• Excellent communication and stakeholder management capabilities
• Ability to influence without authority and operate effectively in matrixed organizations
• Self-driven, organized, and able to manage multiple priorities.