Snowflake Architect or Data Architect 16003

Cephas Consultancy Services Private Limited; Houston (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Cephas Consultancy Services Private Limited in Houston, TX is seeking a Snowflake Architect or Data Architect to design, build, and scale a modern cloud data platform centered on Snowflake and AWS. The ideal candidate will combine deep data engineering fundamentals with governance and ontology-driven modeling to deliver trusted data products.

You will work on strategic initiatives using Snowflake, AWS, Iceberg managed tables, Snowflake Catalog and Horizon, Informatica, and dbt to enable

Qualifications

• Extensive experience in data engineering, modeling, and cloud platform development.
• Hands-on Snowflake implementation, optimization, and security controls.
• Experience with AWS cloud environments and data integration platforms.
• Proficiency with dbt for transformations and analytics engineering workflows.
• Familiarity with Iceberg and open table formats for scalable data lakes.
• Knowledge of ontology, semantic modeling, and governance concepts.
• Strong SQL and Python skills; stakeholder collaboration.

Responsibilities

• Design, build, and maintain scalable data pipelines across data sources.
• Develop ingestion and ELT processes using Informatica.
• Create transformation logic with dbt including testing and docs.
• Design data structures in Snowflake and manage warehouse patterns.
• Collaborate with AWS services to support data products.
• Implement data governance, lineage, and quality checks.
• Support analytics, BI, and AI use cases with trusted data.

Skills

Data engineering

Data modeling

ETL/ELT

Snowflake

AWS

Informatica

dbt

Apache Iceberg

Data governance

Ontology/semantic modeling

SQL

Python

Tools

Snowflake Catalog

Snowflake Horizon

dbt (analytics engineering)

Job description

Snowflake Architect or Data Architect 16003

Cephas Consultancy Services Private Limited Houston, Texas, United States

About this position

• Positions:2 Full Time
• Experience
• 12 - 18 Years

Job Description

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

Role Summary

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

This role will support strategic data initiatives usingSnowflake, 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 usingInformatica, aligning with enterprise standards and existing in-house capabilities.

Build transformation logic usingdbt, including modular models, testing, documentation, and deployment workflows.

Design and manage data structures inSnowflake, with Snowflake positioned as the central strategic data platform.

Work withAWS-based data services and infrastructure, supporting applications and data products running in the organization’s AWS environment.

Support data architecture usingIceberg managed tables, including open table formats, interoperability, cataloging, and governed access patterns.

UseSnowflake CatalogandSnowflake Horizonto 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 withSnowflake, including data modeling, performance optimization, access controls, and scalable warehouse/lakehouse patterns.
• Experience working inAWScloud environments.
• Experience withInformaticaor similar enterprise data integration platforms for extract-load and ingestion patterns.
• Experience withdbtfor data transformations, testing, documentation, and analytics engineering workflows.
• Understanding ofApache Icebergor 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 ofontology, 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 withSnowflake CatalogandSnowflake Horizon.
• Experience building governed data products for analytics, AI, or application use cases.
• Experience with enterprise governance tooling, especiallyInformatica 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.

Ideal Candidate Profile

The ideal candidate is a hands-on Data Engineer who can build reliable pipelines and data products while also understanding the meaning and structure of enterprise data. They are comfortable working acrossSnowflake, AWS, Informatica, dbt, Iceberg, Snowflake Catalog, and Horizon, and can help connect technical implementation with business semantics, ontology, governance, and reusable data strategy.

They understand that data engineering is not only about moving data, but also about making data trusted, discoverable, governed, and meaningful across the enterprise.