Data Architect

Our client is seeking a Senior Data Architect to lead the design of scalable, secure, and AI-ready data environments that support complex analytics, machine learning, and modern data platform initiatives. The ideal candidate is a hands-on technical leader who can translate ambiguous business needs into clear architecture, guide engineering teams through execution, and communicate effectively with both technical and non-technical stakeholders., * Lead end-to-end data architecture for complex programs, including data modeling, platform design, integration patterns, governance structures, and scalable data delivery approaches.

• Design conceptual, logical, and physical data models that support analytics, reporting, AI, and modern data product development.
• Architect cloud-native data solutions using AWS services such as S3, Glue, Redshift, Athena, Lake Formation, Kinesis, MSK, Lambda, Step Functions, and EventBridge.
• Design and implement ETL/ELT workflows with strong attention to data quality, lineage, monitoring, observability, and long-term maintainability.
• Evaluate and recommend data platform technologies, including warehouse, lakehouse, streaming, orchestration, and governance tools based on program needs and technical trade-offs.
• Establish data contracts, interface standards, access controls, and integration patterns that ensure reliable data movement across source systems, pipelines, and consuming applications.
• Design data foundations for AI and LLM use cases, including document ingestion, preprocessing, enrichment, embedding workflows, vector search, and RAG-enabled architectures.
• Define data governance frameworks, including ownership, classification, retention, access policies, lineage, and metadata management practices.
• Partner with engineering, DevOps, platform, product, and machine learning teams to ensure architectures are secure, cost-conscious, operationally sustainable, and aligned with delivery goals.
• Lead client discovery sessions, translate business and operational needs into actionable technical recommendations, and present architecture decisions to diverse stakeholder groups.
• Own data architecture workstream planning, including task breakdown, sequencing, dependency mapping, estimation, delivery reviews, and Jira-based project coordination.
• Mentor data engineers and contribute to internal architecture standards, reusable patterns, documentation, onboarding resources, and technical best practices.

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field, or equivalent professional experience.
• 6+ years of hands-on data engineering, data architecture, or related technical experience, including senior-level ownership of architecture decisions.
• Strong experience designing scalable data platforms, data warehouses, lakehouses, and analytics-ready data environments.
• Deep hands-on experience with AWS data services, including S3, Glue, Glue Catalog, Redshift, Athena, Lake Formation, Kinesis, MSK, Lambda, Step Functions, and EventBridge.
• Proven ability to create conceptual, logical, and physical data models for complex enterprise-scale data environments.
• Strong understanding of data governance, data quality, lineage, metadata management, access control, and production data reliability practices.
• Experience designing data architectures that support AI, LLM, RAG, vector search, embedding pipelines, and unstructured or document-based data workflows.
• Experience with infrastructure-as-code tools such as Terraform or AWS CDK, along with familiarity with DevOps, DataOps, and cloud deployment practices.
• Demonstrated ability to lead client-facing technical discussions, gather requirements, assess data readiness, and present architectural recommendations clearly.
• Strong technical program leadership skills, including the ability to break down ambiguous initiatives, manage dependencies, guide delivery, and resolve technical trade-offs.
• Excellent written and verbal communication skills with the ability to adjust technical depth for engineers, business stakeholders, and executive audiences.
• Experience mentoring engineers, conducting architecture reviews, and building reusable standards or playbooks for broader team adoption.
• AWS certifications such as Solutions Architect Associate/Professional or Data Engineer Associate are preferred.
• Experience with Databricks, Delta Lake, dbt, data cataloging tools, data mesh, or data product architecture is preferred.
• Consulting, professional services, government, regulated industry, FedRAMP, Public Trust, or security clearance experience is a plus.