Enterprise Snowflake Architect: Data Pipelines & Governance

Staffingine LLC; Houston (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Staffingine LLC seeks a Snowflake Architect to design, build, and optimize scalable data pipelines and Snowflake-based data structures. You will work across AWS services to support AI-enabled use cases and data products, ensuring governance and security are baked into every layer.

Collaborate with data architects, governance teams, analysts, and business stakeholders to convert business concepts into robust data models and reusable data products.

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.
• Ability to work with business stakeholders to define data entities, relationships, metrics, and data product requirements.
• Strong communication, documentation, and problem-solving skills.

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.

Skills

Data engineering

Data modeling

ETL/ELT

SQL

Python

Stakeholder collaboration

Communication

Tools

Snowflake

Informatica

dbt

AWS

Apache Iceberg

Snowflake Catalog/Horizon

Job description

Staffingine LLC seeks a Snowflake Architect to design, build, and optimize scalable data pipelines and Snowflake-based data structures. You will work across AWS services to support AI-enabled use cases and data products, ensuring governance and security are baked into every layer.

Collaborate with data architects, governance teams, analysts, and business stakeholders to convert business concepts into robust data models and reusable data products.