Technology

Data Architect (Snowflake)

Prudent Technologies and ConsultingHouston, TX🇺🇸United StatesPosted Sep 28, 2026

Why This Role Stands Out

Leverage your expertise to architect and build cutting-edge data solutions within Snowflake and AWS, driving strategic data initiatives for a reputable consulting firm. This on-site role in Houston is ideal for a mid-senior professional eager to shape data platforms and collaborate across diverse teams, offering significant opportunities for impact and professional development. Embrace this chance to advance your career and contribute to innovative data strategies.

Quick Overview

Seniority

Mid Senior

Work mode

On Site

Location

Houston, TX, United States

Posted

1 week ago

AWSSnowflakedbt

Job Description

Role: Snowflake Architect Location: Houston, TX (Onsite)
Contract- Hire / Full Time Key Responsibilities

Design, build, and maintain scalable data pipelines across structured, semi-structured, and unstructured data sources.
Develop data ingestion and extract-load processes using Informatica, aligning with enterprise standards and existing in-house capabilities.
Build transformation logic using dbt, including modular models, testing, documentation, and deployment workflows.
Design and manage data structures in Snowflake, with Snowflake positioned as the central strategic data platform.
Work with AWS-based data services and infrastructure, supporting applications and data products running in the organization s AWS environment.
Support data architecture using Iceberg managed tables, including open table formats, interoperability, cataloging, and governed access patterns.
Use Snowflake Catalog and Snowflake Horizon to support metadata management, data discovery, governance, lineage, policy enforcement, and trusted data sharing.
Collaborate with data architects, governance teams, analysts, application teams, and business stakeholders to define trusted data products.
Work with domain experts to understand business concepts, entities, relationships, and terminology.
Support ontology-driven modeling, including entity definitions, taxonomies, relationships, business glossaries, and semantic mappings.
Translate business and domain concepts into logical data models, physical data models, and reusable data products.
Implement data quality checks, validation rules, lineage, observability, and governance controls.
Support data products and applications such as news intelligence, asset intelligence, analytics, and AI-enabled use cases.
Ensure data solutions meet enterprise requirements for security, privacy, access control, performance, and reliability.