Snowflake Data Architect

YO AI Labs; Houston (TX); On-site; USD 130,000 - 180,000; Full time

Job summary

YO AI Labs is hiring a Snowflake Data Architect in Houston, USA. This role involves designing scalable data pipelines and managing data structures in Snowflake as the strategic data platform.

The ideal candidate will have extensive experience in data architecture, governance, and knowledge of cloud services, particularly in the Oil & Natural Gas sector. Proven experience with Snowflake, Informatica, and AI technologies is essential for success in this role.

Qualifications

• 12-20 years of experience in data engineering, modeling, ETL/ELT, and cloud data platform development.
• Hands-on experience with Snowflake including data modeling and performance optimization.
• Experience working in AWS cloud environments.

Responsibilities

• Design, build, and maintain scalable data pipelines across varied data sources.
• Develop data ingestion and extract-load processes using Informatica.
• Build transformation logic using dbt and manage data structures in Snowflake.

Skills

Snowflake Data Architecture experience

Data Governance & Metadata Management expertise

AWS services knowledge

SQL skills

Python or another data engineering language

Experience with Informatica

Experience with dbt

Oil & Natural Gas Midstream domain experience

Claude AI / Generative AI experience

Job description

Job Description

• Job title: Snowflake Data Architect
• Experience: 12-20 Years
• Location: Houston, USA
• Job Type: Full-Time

Must Haves

• Strong Snowflake Data Architecture experience.
• Data Governance & Metadata Management expertise.
• Understanding of Ontology & Semantic Modeling.
• Working knowledge of AWS services such as S3, Glue, Lambda, Athena, EMR, Redshift, and cloud-based data architectures.
• Oil & Natural Gas Midstream domain experience (Mandatory).
• Claude AI / Generative AI experience (Mandatory).

Qualifications

• Strong experience in data engineering, data modeling, ETL/ELT, and cloud data platform development.
• Hands‑on experience with Snowflake, including data modeling, performance optimization, access controls, and scalable warehouse/lakehouse patterns.
• Experience working in AWS cloud environments.
• Experience with Informatica or similar enterprise data integration platforms for extract-load and ingestion patterns.
• Experience with dbt for data transformations, testing, documentation, and analytics engineering workflows.
• Understanding of Apache Iceberg or open table formats, including managed tables, schema evolution, interoperability, and catalog‑based access.
• Familiarity with data cataloging, governance, lineage, metadata management, and policy‑driven data access.
• Understanding of ontology, semantic modeling, taxonomies, business glossaries, or knowledge graph concepts.
• Strong SQL skills and experience with Python or another data engineering language.

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.
• 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.