Data Architect

Prudent Technologies and Consulting, Inc.; Houston (TX); On-site; USD 130,000 - 160,000; Full time

Job summary

Prudent Technologies and Consulting, Inc. in Houston, TX seeks a Data Architect/Engineer to design, build, and scale a cloud data platform centered on Snowflake and AWS.

The role emphasizes ontology-driven data models, governance, metadata management, and policy-based data access to deliver trusted data products for analytics and AI. Responsibilities include designing scalable pipelines, implementing Informatica and dbt workflows, and leveraging Iceberg tables, Snowflake Catalog, and Horizon for

Qualifications

• Experience in data engineering, modeling, ETL/ELT, and cloud data platform development.
• Hands-on Snowflake experience, including modeling, performance optimization, access controls, and scalable warehouse/lakehouse patterns.
• Experience 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 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

AWS

Snowflake

Governance

Ontology modeling

Metadata management

Data cataloging

Knowledge graph concepts

Stakeholder collaboration

Tools

Snowflake

AWS

Informatica

dbt

Iceberg

Snowflake Catalog

Snowflake Horizon

Job description

Focus: Snowflake, AWS, Iceberg, Data Governance, and Ontology-Driven Data Models

Data Architect- 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. + Claude Mandatory + AWS working knowledge + Oil and Natural Gad Mid Stream Domain

Role Summary

We are looking for a Data Engineer to help design, build, and scale a modern cloud data platform centered on Snowflake and AWS. The ideal candidate has strong data engineering fundamentals, experience with enterprise data platforms, and the ability to work with ontologies, semantic models, metadata, and governed data products.

This role will support strategic data initiatives using Snowflake, AWS, Iceberg managed tables, Snowflake Catalog, Snowflake Horizon, Informatica, and dbt. The Data Engineer will help create trusted, reusable data assets that support applications, analytics, AI, and business intelligence use cases.

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.

Required Skills

• 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.

Preferred Skills

• Experience with Snowflake Catalog and Snowflake Horizon.
• Experience building governed data products for analytics, AI, or application use cases.
• Experience with enterprise governance tooling, especially Informatica governance capabilities.
• Experience with RDF, OWL, SHACL, SPARQL, graph databases, or knowledge graph platforms.
• Experience designing semantic layers, business glossaries, metadata models, or domain ontologies.
• Experience with CI/CD, Git, automated testing, and deployment workflows for data pipelines.
• Experience with data observability, lineage tracking, data contracts, and data quality frameworks.
• Experience working in complex enterprise data environments with multiple systems, domains, and stakeholder groups.