Data Architect

Job Summary

We are seeking an experienced Data Architect to design and deliver large-scale data platforms, data models, and pipelines. The ideal candidate will have strong hands-on technical expertise in SQL/Python, enterprise data architecture, and modern AI data foundations, including RAG and agentic workflows.

Key Responsibilities:

• Design and implement scalable data platforms, conceptual/logical/physical data models, and enterprise data pipelines.
• Develop and optimize data integration solutions using ETL/ELT, batch processing, streaming, and Change Data Capture (CDC) patterns.
• Design data foundations for RAG and agentic AI workflows, including document processing, metadata management, chunking, embeddings, and vector indexing.
• Ensure data quality, freshness, lineage, governance, security, and access controls to improve retrieval accuracy and reliability.
• Design and implement semantic models and modern data warehouse/lakehouse architectures.
• Lead data discovery workshops with business stakeholders, data teams, and engineers to translate business requirements into practical data solutions.
• Troubleshoot production data issues hands-on and explain root causes and resolutions.
• Mentor engineers on data modeling, pipeline development, governance, and AI data preparation.
• Establish reusable integration patterns, data modeling standards, and best practices.
• Communicate complex data flows, architectural decisions, and technical trade-offs clearly to business and technical stakeholders.

Required Skills and Experience:

• Proven experience designing and delivering large-scale data platforms, models, and pipelines.
• Strong hands-on expertise in SQL and Python, including production troubleshooting.
• Strong understanding of AI/RAG/agentic architectures and their underlying data requirements.
• Experience with document processing, metadata, chunking strategies, embeddings, and vector indexing.
• Expertise in conceptual, logical, and physical data modeling.
• Experience with ETL/ELT, batch processing, streaming, and CDC patterns.
• Knowledge of data warehouses, lakehouses, semantic models, data lineage, quality, governance, and access controls.
• Excellent customer-facing communication and stakeholder management skills.
• Demonstrated leadership, mentoring, and ability to collaborate with cross-functional delivery teams.

Ideal Candidate Profile:

A hands-on Data Architect who combines enterprise data architecture expertise with modern AI data engineering knowledge, can lead customer-facing architecture discussions, resolve complex production issues, and guide engineering teams toward scalable, reusable solutions.