Senior Data Architect

We are seeking an experienced Senior Data Architect to lead the design and evolution of modern cloud-based data ecosystems. In this role, you will architect scalable, secure, and high-performing data platforms that support advanced analytics, AI/ML initiatives, real-time data processing, and business intelligence across the enterprise.

The ideal candidate brings deep expertise in cloud-native data architectures, traditional database technologies, data governance, and AI-enabled solutions. You'll work closely with engineering, architecture, and business teams to build robust data foundations that support everything from operational reporting to Retrieval-Augmented Generation (RAG), semantic search, and generative AI applications.

What You'll Do

Cloud Data Architecture

• Design and implement modern data platforms using cloud-native services and data engineering best practices.
• Build scalable data pipelines supporting ingestion, transformation, storage, and analytics workflows.
• Define data storage, partitioning, optimization, and lifecycle management strategies to maximize performance and cost efficiency.
• Establish architecture standards for lakehouse, warehouse, and operational data environments.

AI, Machine Learning & RAG Enablement

• Design data foundations that support machine learning, predictive analytics, and generative AI workloads.
• Develop architectures for Retrieval-Augmented Generation (RAG), semantic search, embeddings, and vector-based knowledge retrieval.
• Define best practices for prompt management, contextual retrieval, model grounding, and evaluation frameworks.
• Support enterprise AI initiatives through scalable and governed data access strategies.

Enterprise Data Management

• Design and govern enterprise data models and integration frameworks.
• Provide expertise in relational and non-relational database technologies, including performance tuning, scalability, availability, and disaster recovery.
• Establish standards for data quality, consistency, interoperability, and lifecycle management.
• Support data lake, warehouse, and operational data store architectures.

Integration & Application Architecture

• Define standards for APIs, data contracts, and system integrations.
• Support ingestion and integration of data from enterprise applications, operational systems, external partners, and streaming sources.
• Collaborate with application and platform teams to ensure data architectures support scalable and efficient business solutions.
• Drive consistency across enterprise data integration patterns and services.

Data Governance & Security

• Implement enterprise data governance practices, including metadata management, lineage tracking, data cataloging, and stewardship.
• Establish security frameworks covering encryption, access management, masking, tokenization, and privacy protection.
• Ensure compliance with applicable regulatory and organizational data requirements.
• Define secure approaches for AI data usage, model inputs, outputs, and information access.

Data Quality & Observability

• Develop monitoring frameworks for data quality, reliability, and performance.
• Establish data service level objectives, quality rules, and operational metrics.
• Identify opportunities to optimize storage, processing, and infrastructure costs.
• Drive continuous improvement across platform performance and operational efficiency.

Technical Leadership

• Develop target-state architectures, roadmaps, and implementation strategies.
• Lead architecture reviews, technical assessments, and proof-of-concept initiatives.
• Mentor engineers, analysts, and architects on data engineering and architectural best practices.
• Communicate complex technical concepts effectively to both technical and business stakeholders.
• Champion innovation, engineering excellence, and continuous learning across teams.

Are you passionate about building next-generation data platforms that power analytics, AI, machine learning, and enterprise-scale decision-making?, * Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field.

• 10+ years of experience designing and delivering enterprise data solutions.
• 5+ years of experience building cloud-based data platforms in production environments.
• Strong expertise in:
• Data Architecture
• Data Engineering
• Data Modeling
• Data Warehousing
• Lakehouse Architectures
• Cloud Data Platforms
• Extensive experience supporting AI/ML, advanced analytics, and large-scale data processing initiatives.
• Strong SQL and Python development skills.

Preferred

• Experience designing enterprise-scale AI, machine learning, and RAG solutions.
• Experience with vector databases, semantic search, and knowledge retrieval systems.
• Exposure to business intelligence and data visualization platforms.
• Experience working with regulated data environments.
• Relevant cloud architecture or data platform certifications.

Core Competencies

• Data Architecture & Engineering
• Cloud Platform Design
• Lakehouse & Data Warehouse Solutions
• AI/ML Data Foundations
• Retrieval-Augmented Generation (RAG)
• Data Governance & Security
• Enterprise Integration
• Data Modeling & Optimization
• Technical Leadership
• Strategic Architecture Planning
• Cost Optimization & FinOps
• Stakeholder Management